Location: Sofia
About us
The Financial Times is one of the world’s leading news organisations, globally recognised for its authority, integrity and accuracy, with a mission to deliver quality information and services worldwide.
At the FT, curiosity thrives and ambitious thinking is rewarded. Here, you’re given the chance to reach millions, create work that matters and deliver impartial journalism in a polarised world.
In our warm, collaborative culture, you’ll connect with a diverse community of experts who support your growth, career aspirations and wellbeing.
Your future at the FT will be filled with opportunities that challenge and inspire you. With no fixed path, you’ll discover new skills and forge a career that can take you anywhere.
Build a newsworthy career at the FT.
Our commitment to diversity, equity and inclusion
We believe everyone should have a fair opportunity to contribute, succeed, and reach their full potential. That means ensuring everyone is heard, respected, and valued, while identifying and removing barriers that may get in the way. Our commitment is to be an employer role model, grounded in inclusion and fairness for all.We want every application to receive fair and thoughtful consideration; therefore, all applications are reviewed by a member of our recruitment team, not by AI.
The role
The Analytics Engineer is responsible for bridging the gap between data engineering and data analytics by maintaining and developing scalable data models and solutions that support finance, B2B, and B2C teams. The role plays a key part in delivering value through modern data stack technologies (including dbt), supporting cloud migration efforts, ensuring data quality, and maintaining the performance of analytical data pipelines.
Key responsibilities
Collaborate with stakeholders across departments to design and implement robust data models and BI solutions.
Build, test, and maintain data transformations using dbt (data build tool).
Implement software engineering best practices for data, including version control, CI/CD, and automated testing.
Deliver day-to-day support and project-related tasks for the data and BI infrastructure.
Develop and maintain scalable, maintainable, and well-documented data pipelines.
Identify and resolve issues across ETL/ELT processes and data pipelines.
Required skills and experience
Essential
3+ years of experience in Analytics Engineering, BI, or Data Engineering roles.
Strong proficiency in SQL, including complex queries and performance tuning.
Hands-on experience with dbt for data transformation and modeling.
Understanding of data migration to cloud platforms such as AWS (Redshift) or GCP (BigQuery).
Familiarity with database design, version control (e.g. Git/GitHub), and CI/CD practices.
Experience with ETL/ELT tools (e.g. Airflow,DBT).
Personal skills
Strong analytical thinking and problem-solving abilities.
Effective communication skills and ability to collaborate across teams.
Attention to detail and focus on continuous improvement and data quality.
Adaptability to fast-paced environments.
Often used technology stacks and tools
Databases & Data Warehouses: AWS Redshift, BigQuery, MS SQL Server.
Data Transformation: dbt (data build tool).
ETL & Data Processing: Airflow.
BI & Data Visualization Tools: Looker.
Programming & Scripting: SQL, Python.
Version Control & DevOps: GitHub, CI/CD pipelines.
Cloud Platforms: AWS, GCP.
What’s in it for you? Our benefits
Annual bonus scheme
25 days paid leave
24/7 Employee Assistance Program
Life Insurance
Enhanced Parental Leave policy
Food Allowance
Multisport Card
Both in house and external training programs
Your own training dedicated budget (for conferences, courses etc.)
We currently operate a
hybrid model
which requires staff to work onsite 50% of the time, subject to role requirements & regular review. While flexible working requests will be considered, not all patterns are suitable for all roles. We believe this balanced approach supports flexibility and protects our culture, making collaboration and communication easier, building stronger relationships and team cohesion, and supporting peer learning. We reserve discretion on reasonable notice to change this approach either generally or for specific individuals or teams.
Accessibility
We are a disability confident employer and Valuable 500 signatory.
Please let us know if you require any reasonable adjustments/personalisation as part of the application process or to enable you to attend an interview. If you would like to discuss your requirements or have any questions, email talent@ft.com and a member of our team will be happy to help.
Further information
At the FT, we embrace innovation and the use of technology and appreciate that individuals may leverage AI tools as part of their job application process. Whilst we are happy for you to use AI to assist with your application, it is essential that all information provided is authentic and accurately represents your skills, experience, and qualifications.
Candidates should be aware that the use of AI throughout the application process may be monitored to ensure a fair and transparent hiring process for all.
Please beware of fraudulent job postings and offers claiming to be from the Financial Times. All legitimate opportunities will direct you to apply through the official Financial Times careers site, and the FT will never ask for financial information, payments, or referrals to third parties during the hiring process. If you have any concerns about the legitimacy of a job posting or suspect any scam activity, please contact talent@ft.com.
Interested in the FT but don’t see the right role yet? Join our Talent Community to receive exclusive updates, featured jobs, and insights into working at the FT.
#LI-MG1
Location: Belgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Monterrey, Mexico; Montevideo, Uruguay; Odesa, Ukraine; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.BG, Bulgaria; Remote.CO, Colombia; Remote.GE, Georgia; Remote.PL, Poland; Riga, Latvia; Rosario, Remote.LATAM-country; Sofia, Bulgaria; Tbilisi, Georgia; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland; Yerevan, Armenia
We are looking for a Senior Data/Analytics Engineer to work at the intersection of data engineering and business intelligence. In this role, you will own dbt models in Snowflake from design through deployment and build Tableau reporting solutions on top of them. You will have a direct impact on how portfolio, client, and financial data is modeled, governed, and presented across the organization.
This position requires availability aligned with the EST time zone or at least a four hour overlap with EST working hours.
The project involves the development and expansion of a centralized, scalable data ecosystem. Having successfully ingested the initial data source, the team is now moving into a high-growth phase to integrate multiple high-value financial and operational data streams. The goal is to provide C-level executives and advisors with a unified, reliable reporting layer for strategic decision-making.
Design, develop, and maintain dbt Core projects, including staging, intermediate, and mart layers
Build incremental models, snapshots, macros, reusable Jinja components, and testing frameworks
Ensure data quality through testing, documentation, lineage management, and version controlled development practices
Design dimensional data models and reporting structures for portfolio, client, and financial analytics
Develop and maintain data ingestion pipelines into Snowflake, including API based integrations
Orchestrate and monitor data workflows using Prefect
Integrate and standardize data from third party platforms such as Addepar, NetSuite, Salesforce, Morningstar, and UKG through Workato
Create and maintain Tableau dashboards, published data sources, and reporting assets
Optimize Snowflake performance and cost efficiency through query tuning, warehouse management, and data architecture improvements
Collaborate with business stakeholders to translate reporting and analytics requirements into scalable data solutions
5+ years of experience in Data Engineering or Analytics Engineering
Hands on experience with dbt Core in production environments
Experience designing data models, incremental strategies, snapshots, macros, Jinja templates, tests, and documentation in dbt
Strong experience with Snowflake, including performance optimization and cost management
Advanced SQL skills
Strong understanding of dimensional modeling and star schema design
Hands on experience building Tableau dashboards and data sources
Experience with calculated fields, Level of Detail expressions, extracts, live connections, and dashboard performance optimization
Experience with ETL and ELT architectures and API based data ingestion
Experience with workflow orchestration tools such as Prefect or Apache Airflow
Understanding of financial services, wealth management, investment management, or portfolio data structures
dbt Analytics Engineering Certification
Experience within wealth management or investment management environments
Experience with Workato or comparable integration platforms
Experience working with Addepar, Morningstar, or Bloomberg data
Python development experience for data engineering workflows
Experience implementing CI/CD practices for dbt projects using GitHub Actions or similar tools
Knowledge of regulatory and privacy requirements related to financial data management and reporting
Задачи:
— Позиционирование и обмен сообщениями.
— Основное позиционирование, определение категории и иерархия сообщений для целевых групп клиентов и персон.
— Документация по целевым группам клиентов и персонам, которая используется, а не хранится в архиве.
— Уровень обмена сообщениями при запуске новых продуктов и функций, включая внутреннее внедрение, позволяющее сотрудникам на местах успешно их продавать.
— Конкурентная разведка и анализ побед/поражений.
— Структурированная программа интервью по анализу побед/поражений с ежеквартальными отчетами.
— «Живые» карты противостояния.
— Мониторинг позиционирования, ценообразования и изменений в продуктах конкурентов, а также разработка контрпозиционирования.
— Поддержка продаж.
— Основная концепция презентации, сюжетная линия демонстрации и система обработки возражений.
— Компоненты обмена сообщениями при адаптации новых сотрудников.
— Регулярные еженедельные встречи с руководством отдела продаж — а не ежеквартальные проверки.
— Прямая поддержка в конкурентных и корпоративных сделках: запросы предложений, оценки безопасности и технических характеристик, стратегии вытеснения конкурентов.
— Связи с рынком и аналитиками.
— Импровизированная концепция взаимодействия с Gartner, Forrester и влиятельными лицами в отрасли, чтобы звонок покупателя аналитику стал ускорителем, а не препятствием.
— Использование структурированной информации о рынке и покупателях для определения приоритетов в разработке продукта.
Требования:
— Опыт работы в продуктовом маркетинге от 4 до 8 лет, или эквивалентное сочетание продуктового маркетинга с маркетинговой аналитикой, маркетингом или операциями с данными, технической поддержкой продаж, аналитическим консалтингом или управлением продуктами на основе данных.
— Свободное владение маркетинговыми данными и измерениями: модели атрибуции, тестирование инкрементальности, MMM, управление данными и таксономия, хранилища данных и ETL/ELT — включая области, где каждый из них действительно слаб.
— Опыт продаж B2B SaaS маркетинговым или информационным компаниям.
— Опыт работы с поставщиками маркетинговой аналитики, маркетинговых технологий, измерений, CDP, BI и инфраструктуры данных является эталонным.
— Доказательства того, что вы реализовали продукт, а не просто задокументировали его: позиционирование, изменившее веб-сайт и презентацию, открытые торговые карты, программа побед/поражений, которая просуществовала более второго квартала.
— Умение писать тексты, выдерживающие проверку скептически настроенным техническим покупателем — утверждения и доказательства, а не нагромождение прилагательных.
— Уверенное взаимодействие с отделом продаж: еженедельные совещания, обзоры сделок, прямые звонки, прямая обратная связь.
— Желательно: практический опыт работы с SQL, DBT или BI, достаточный для самостоятельной проверки заявлений.
— Опыт маркетинга возможностей ИИ без излишней шумихи.
— Опыт работы с аналитиками.
— Опыт работы в агентстве или с крупными брендами.
— Глубокие знания в фармацевтической и медицинской отраслях, финансовых услугах, розничной торговле и электронной коммерции, или игровой индустрии.
— Не подходит, если: ваш продуктовый маркетинг в основном сосредоточен на логистике запуска и контент-планах; вам нужна полностью укомплектованная команда и готовая система брендинга для эффективной работы; вам некомфортно, когда на совещании по сделке вам говорят, что ваши сообщения не сработали.
Условия:
— Сложные и интересные задачи
— Работа в международной команде
— Разработка и передовые технологии
— Медицинское страхование
Location: Los Angeles, USA
The Insights discipline helps empower Rioters' decision-making to be more data-informed and put player experience at the forefront. We're an interdisciplinary group of scientists, consultants, and strategists from all sorts of backgrounds who join together to represent and advocate for players around the world. We believe that illuminating the globally diverse experiences, behaviors, and needs of players is critical to Riot living up to our player-focused mission. We're a group united by our love of games, science, and helping others succeed.
As a
Principal Insights Analyst on League of Legends
, you’ll join the League Insights team – a group of researchers, analysts, ML engineers and data engineers, responsible for solving complex problems and enabling Rioters to make difficult decisions with confidence.
You’ll tackle some of the most complex and ambiguous problems facing League and advise senior leaders on key product and business decisions. This role will have a particular focus on game economy and monetization systems, while also helping evolve how our team conducts analytics work in an increasingly AI-enabled environment. You’ll combine strong product judgment, advanced analytics, and technical expertise to solve difficult problems, build scalable analytical workflows, and mentor analysts across the team.
Responsibilities:
Own and lead some of League’s most complex Insights problem spaces, identifying and prioritizing the right questions, navigating ambiguity, and driving work from problem framing through strategic recommendation.
Develop deep analytical perspectives on League’s economy to inform monetization strategy, across questions such as content strategy, spender lifecycle and segmentation, purchasing behavior, product incrementality and cannibalization, and long-term monetization health.
Apply advanced analytical methods to uncover the drivers of player behavior and product performance, identify opportunities and risks, and deepen understanding of complex product questions.
Develop reusable AI-enabled and agentic analytics workflows, tooling, and reporting approaches that improve the speed, consistency, and reliability of analysis.
Help evolve the League Insights analytics ecosystem and standards for an AI-enabled future, including new approaches to interactive reporting, self-service analytics, and AI-assisted analysis.
Partner closely with data engineers to align evolving data foundations with downstream analytical workflows, reporting needs, and AI-enabled use cases.
Shape product and business decisions through data-driven recommendations and trusted partnership with product teams and League leadership.
Serve as a craft leader across Insights, setting quality standards, mentoring senior practitioners, and advancing analytical capabilities across the discipline.
Required Qualifications:
BA/BS in Statistics, Data Science, Computer Science, Economics, Applied Mathematics, or a related field
9+ years of experience in analytics, data science, business intelligence, consulting, or related roles involving complex quantitative analysis
Demonstrated ability to own and solve highly complex, ambiguous product or business problems, translating analytical work into strategic recommendations
Strong proficiency with SQL and Python, with experience building analytical pipelines and data models in modern data environments such as Databricks and DBT
Hands-on experience developing AI-enabled or agentic analytics workflows, with demonstrated impact on how analysis, reporting, or self-service analytics are performed
Deep expertise in analytical methods, with the ability to select and apply advanced approaches to understand complex player, product, and business questions
Strong product and business judgment, with experience using analytics to inform product, monetization, or other strategic decisions
Proven ability to lead complex cross-functional work, influence senior stakeholders, and elevate analytics craft through mentorship, standards, or technical leadership
Desired Qualifications:
Advanced degree in Economics, Statistics, Data Science, Computer Science, or a related field
Experience analyzing game economies or monetization ecosystems
Experience working on live-service games or other complex digital products with interconnected engagement and monetization systems
Experience developing and scaling AI-enabled or agentic analytics workflows and self-service analytics beyond traditional BI tools, including reusable applications, tooling, standards, or team practices
Experience applying modern software development practices to analytics workflows, such as version control, code review, testing, and modular development
Strong familiarity with League of Legends as a player
For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!
Our Perks:
Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our
benefits pages
for more information.
At Riot Games, we
put players first
. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.
It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
Safeguarding confidential and sensitive Company data
Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
Accessing Company assets, secure digital systems, and networks
Ensuring a safe interactive environment for players and other Rioters
These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.
Location: Remote - Canada
What We’re Building
Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!
If you want to see what we’ve been up to, please check out these
blog posts
and Honeycomb.io
press releases
.
Who We Are
We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live
our values
every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers.
How We Work
We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote
About the problem space
AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working."
Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering.
Little more about the team:
You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place.
What you'll do
You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first.
Ship automated workflows end to end
Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't.
Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work."
Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring.
Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing.
Build the shared substrate as you go
Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance.
Build on the Data team's existing infrastructure rather than standing up parallel systems.
Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively.
Make the company fluent
Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns.
Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating.
Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows.
Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked.
Keep it safe and governable
Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment.
Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines.
What you'll bring
Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily.
Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable.
The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work.
A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making.
Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk.
Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are.
Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does.
Nice to have
SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling).
Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases.
Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis.
Change management experience across a distributed, multi-function company.
Interest in external evangelism — writing, speaking, podcasts, peer groups.
Base Salary based on level of experience
$310,000
—
$360,000 CAD
What you'll get when you join the Hive:
A stake in our success - generous equity with employee-friendly stock program
It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
Time to recharge with unlimited PTO
A distributed-first mindset and culture (really!)
Home office, co-working, and internet stipend
Full benefits coverage for employees, with additional coverage available for dependents
Up to 16 weeks of paid parental leave, regardless of path to parenthood
Annual development allowance
And much more...
Please note we cannot currently sponsor or support visa transfers at this time.
Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.
Phishing and Recruitment Scam Warning:
We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you:
All communications will come from an
@honeycomb.io
email address
We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—
never personal accounts like Gmail or Yahoo
.
Our recruiting process will
never
ask you to provide financial or sensitive personal information, including but not limited to:
Social security or tax identification numbers
Credit card numbers
Bank account information
Diversity & Accommodations:
We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams.
We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know.
As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback.
Privacy Notice:
If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes.
For more information regarding our privacy practices please see the
Honeycomb Privacy Notice
.
If you do not want us to retain your information, or want us to update it, please contact
privacy@honeycomb.io
. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.
Location: Remote - United States
What We’re Building
Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!
If you want to see what we’ve been up to, please check out these
blog posts
and Honeycomb.io
press releases
.
Who We Are
We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live
our values
every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers.
How We Work
We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote
About the problem space
AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working."
Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering.
Little more about the team:
You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place.
What you'll do
You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first.
Ship automated workflows end to end
Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't.
Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work."
Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring.
Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing.
Build the shared substrate as you go
Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance.
Build on the Data team's existing infrastructure rather than standing up parallel systems.
Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively.
Make the company fluent
Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns.
Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating.
Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows.
Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked.
Keep it safe and governable
Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment.
Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines.
What you'll bring
Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily.
Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable.
The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work.
A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making.
Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk.
Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are.
Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does.
Nice to have
SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling).
Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases.
Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis.
Change management experience across a distributed, multi-function company.
Interest in external evangelism — writing, speaking, podcasts, peer groups.
Base Salary based on level of experience
$225,000
—
$265,000 USD
What you'll get when you join the Hive:
A stake in our success - generous equity with employee-friendly stock program
It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
Time to recharge with unlimited PTO
A distributed-first mindset and culture (really!)
Home office, co-working, and internet stipend
Full benefits coverage for employees, with additional coverage available for dependents
Up to 16 weeks of paid parental leave, regardless of path to parenthood
Annual development allowance
And much more...
Please note we cannot currently sponsor or support visa transfers at this time.
Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.
Phishing and Recruitment Scam Warning:
We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you:
All communications will come from an
@honeycomb.io
email address
We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses—
never personal accounts like Gmail or Yahoo
.
Our recruiting process will
never
ask you to provide financial or sensitive personal information, including but not limited to:
Social security or tax identification numbers
Credit card numbers
Bank account information
Diversity & Accommodations:
We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams.
We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know.
As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback.
Privacy Notice:
If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes.
For more information regarding our privacy practices please see the
Honeycomb Privacy Notice
.
If you do not want us to retain your information, or want us to update it, please contact
privacy@honeycomb.io
. Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.
Location: New York; San Francisco
Workplace: OnSite
ABOUT US:
AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.
Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
ABOUT GTM ENGINEERING:
GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal.
Like the infrastructure beneath the Magic Kingdom https://en.wikipedia.org/wiki/Disney_utilidor_system, much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal.
We bring a product management, growth engineering, and data science approach to GTM, from centralizing our data platform https://deepline.com/blog/gtm-ai-nyc-chris-modal to building agents for account research https://parallel.ai/blog/case-study-modal.
THE ROLE:
We’re looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you’ll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation.
WHAT YOU’LL WORK ON:
- Build and maintain an org map and people graph connecting companies, labs, teams, and individuals to identify researchers, engineers, and early-stage startups, including people beyond our existing users and CRM
- Own identity resolution, enrichment, and CRM schemas so affiliations, roles, and relationships stay accurate, current, and traceable to their sources
- Build GTM data models in Snowflake and dbt connecting people, companies, workspaces, workloads, usage, and revenue, giving reps and agents a shared foundation for customer context
- Partner with RevOps and Marketing to define and implement metrics, data models, and business rules for routing, territory assignments, compensation, pipeline reporting, and attribution
- Partner with Data on usage forecasts and account signals; build reproducible reporting that reconciles actuals, forecasts, human adjustments, and credited attainment
- Build reverse ETL pipelines for ad audiences, lifecycle campaigns, CRM enrichment, outbound, and event outreach, preserving engagement history and campaign eligibility
- Own data quality and system health, from graph coverage and stale enrichment to failed syncs and historical reporting accuracy
- Build the tooling that helps GTM Engineering ship reliably, from development environments, automated tests, and deployments to backups and shared AI agents and skills
YOU MAY BE A FIT IF:
- You’re fluent in SQL and proficient in Python
- You already use AI coding tools and agents to build, debug, and automate your work, and help teammates do the same
- You’ve built data models and production pipelines with tools like Snowflake, dbt, Modal, or Hex
- You have hands-on experience with CRM architecture, integrations, and revenue or marketing operations
- You understand how leads, accounts, opportunities, and revenue move through a business
- You have high attention to detail and a habit of testing, documenting, and monitoring the systems you build
NICE-TO-HAVE:
- Experience with usage-based businesses
Ищем Data Engineer в крупную технологическую компанию, которая разрабатывает высоконагруженные платформенные продукты для международных рынков в entertainment-индустрии. Внутри — развитое data-направление и задачи, связанные с построением и развитием современной платформы данных.
Чем предстоит заниматься:
— проектировать, разрабатывать и развивать data pipelines;
— работать с DWH: моделями данных, слоями, витринами и ETL/ELT-процессами;
— писать и оптимизировать сложные SQL-запросы;
— разрабатывать на Python инструменты и сервисы для работы с данными;
— поддерживать и развивать production-пайплайны;
— работать с большими объемами данных и распределенной обработкой;
— следить за качеством и надежностью данных;
— участвовать в выборе технических решений и развитии data-платформы;
— взаимодействовать с аналитиками, разработчиками и другими продуктовыми командами.
Для Senior-уровня также важен опыт самостоятельного проектирования архитектурных решений и способность брать ответственность за технический подход к задаче.
Требования:
— очень хорошее знание SQL и опыт работы со сложными запросами и большими объемами данных;
— уверенный Python: не только небольшие скрипты, но и production-код, библиотеки или внутренние инструменты;
— хорошее понимание принципов построения DWH;
— опыт проектирования и разработки ETL/ELT-процессов;
— понимание моделирования данных, построения витрин и контроля качества данных;
— умение самостоятельно разбираться в задаче и предлагать техническое решение.
Желательно:
— практический опыт с Airflow: разработка и поддержка DAG, scheduling, retries, backfill, monitoring;
— опыт с dbt или похожими инструментами трансформации данных;
— опыт со Spark и понимание распределенной обработки данных;
— работа с аналитическими СУБД: ClickHouse, Greenplum, Vertica или другими MPP/OLAP-системами.
Будет плюсом:
— Kafka;
— Iceberg;
— Trino;
— Docker / Kubernetes;
— CI/CD;
— понимание подходов Data Mesh;
— участие в open-source или собственные технические проекты.
Условия:
— full-time;
— удаленный формат работы;
— гибкое начало рабочего дня;
— корпоративная техника;
— испытательный срок 3 месяца;
— расширенный пакет бенефитов после испытательного срока: медицинская страховка, бюджет на спорт / языки / дополнительное медицинское покрытие, дополнительные оплачиваемые дни отдыха;
— внутренние технические встречи, тренинги и возможность участия в профессиональных конференциях и обучении.
Процесс:
Знакомство с рекрутером → короткий технический скрининг → технические секции по SQL, DWH и Python → для кандидатов Senior-уровня дополнительная секция по архитектуре и проектированию → встреча с командой.
Задачи:
— строить масштабируемые дата-продукты и пайплайны для машинного обучения, робототехники и бизнес-решений.
Требования:
— опыт работы с SQL, Snowflake, dbt, Python, AWS, Dagster.
Условия:
— null.
Location: New York; San Francisco
Workplace: Hybrid
ABOUT ALCHEMY
Alchemy is the Web3 infrastructure and developer platform that powers millions of users and the world’s most innovative blockchain applications. From enabling $1+ trillion in financial transactions worldwide to scaling L2s and enabling DeFi, Alchemy provides the infrastructure and tools developers need to build reliable, scalable, and accessible experiences.
Trusted by companies like JPMorgan, Stripe, Visa, Franklin Templeton, Nike, and backed by a16z, Coatue, Silver Lake, Lightspeed, and Stanford University, Alchemy is building the foundational layer for a decentralized and AI-enabled Web3 ecosystem. For more information, visit alchemy.com http://alchemy.com.
THE ROLE
Build and run the internal data platform that helps Alchemy understand product usage, revenue, and the cost of serving customers. The existing Data Engineer intake centers on ingestion, Snowflake operations, workflow orchestration, data quality, and collaboration with analytics partners.
You will own ingestion, schema changes, and checks that show whether shared datasets are current and correct. You will work with analytics engineers and data scientists to define those datasets for reporting, analysis, and AI-assisted tools.
WHAT YOU WILL DO
- Build batch and streaming pipelines that connect operational databases, product events, billing systems, and external sources to the internal data platform.
- Make ingestion recoverable through change-data capture, schema-change handling, idempotent processing, and safe backfills.
- Operate and improve Snowflake, including access controls, workload management, query performance, and compute and storage costs.
- Improve orchestration and deployment workflows so engineers can test, ship, and debug pipelines safely.
- Build data-quality checks that detect stale, missing, duplicated, or inconsistent records before they reach downstream consumers.
- Work with analytics partners on shared data models, source definitions, and documentation. Make dataset ownership and upstream dependencies clear.
- Reduce recurring manual work and build reusable tools for self-service data access.
- Participate in production support and incident response for pipelines and the data platform. Restore data flow, reconcile affected datasets, and fix the causes of recurring failures.
WHAT WE ARE LOOKING FOR
- Experience independently building and operating production data pipelines and the infrastructure around them.
- Strong SQL and Python skills, including testing, debugging, and maintainable software design.
- Experience with Snowflake or a comparable warehouse, including performance tuning and access management.
- Experience with workflow orchestration and transformation tools such as Airflow and dbt, or equivalent systems.
- Understanding of data modeling, incremental processing, schema evolution, and data-quality testing.
- The ability to trace a data discrepancy from a downstream report back to its source, explain the cause, and fix it.
- Good judgment about stakeholder needs: turn recurring requests into reusable datasets or tooling, and make trade-offs clear.
Blockchain experience is not required.
HELPFUL EXPERIENCE
- Kafka, database replication, or change-data-capture systems.
- Apache Iceberg, Spark, Trino, or other lakehouse and query technologies.
- Infrastructure as code, data observability, lineage, and disaster recovery.
- Usage metering, billing and revenue data, or semantic layers for self-service analytics.
WHAT SUCCESS LOOKS LIKE
Within three months:
- You own a production pipeline and have shipped an improvement to its freshness, reliability, or operating cost.
- Downstream users can see whether its data is current, recovery procedures have been tested, and a recurring manual request has become a reusable dataset or tool.
BENEFITS & PERKS
🏥 Private Health Insurance
💪 Gym Reimbursement
🚅 Commuter Benefits
🌴 Flexible Time Off
🥙 In-Office Group Meals
🧠 Learning & Development Stipend
🌎 Company Sponsored Conferences & Events
🎧 Books & Audiobook subscription with Bookster https://landing.bookster.ro/
Задачи:
— Решение сложных технических задач и разработка качественных программных систем с применением современных технологий.
— Работа с данными в production-среде.
— Поиск первопричин сбоев.
— Преобразование и валидация больших объёмов данных.
— Взаимодействие с REST-API.
— Загрузка и выгрузка данных.
— Работа с сериализованными и сжатыми форматами.
Требования:
— От 2 лет опыта с Python и библиотеками для работы с данными (pandas, multiprocess, Google Cloud SDK).
— От 2 лет в ETL/ELT-технологиях (REST API, GraphQL, DBT) и оркестрации пайплайнов (Airflow, Astronomer, DBT Cloud).
— Практический опыт со Snowflake.
— Уверенное владение SQL (SQL Server, Oracle, MySQL, BigQuery, Snowflake).
— Работа с форматами JSON, AVRO, XML, CSV, а также со сжатыми и закодированными файлами.
— Навыки загрузки данных через REST-API и выполнения трансформаций.
— Достаточный уровень английского для работы в международной среде.
— Плюсом — опыт проектирования пайплайнов в облачной архитектуре, работы с CI/CD и GIT.
Location: United Kingdom; Poland; Portugal; Spain; Germany; The Netherlands
Workplace: Remote
Recognized on the 2025 Forbes Cloud 100 list https://www.forbes.com/companies/clickhouse/?list=cloud100, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and $250M ARR https://clickhouse.com/blog/clickhouse-tops-250m-arr-and-4000-customers, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company's sustained, accelerating momentum was recently validated by a $400M Series D financing round https://clickhouse.com/blog/clickhouse-raises-400-million-series-d-acquires-langfuse-launches-postgres. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We're on a mission to transform how companies use data. Come be a part of our journey!
We're hiring a Product Manager to own partner integrations at ClickHouse. This role owns how ClickHouse shows up inside the platforms our customers already use: embedded, native experiences across the hyperscalers and developer platforms, and deeper technical integrations with strategic partners like dbt, Fivetran, Hex, and Sigma. There is a growing surface of partner work already in motion, and this role shapes where we invest in co-innovation opportunities.
This is one of the most cross-functional roles at ClickHouse. You'll work across multiple engineering teams, our partnerships and solutions teams, and the partners themselves to deliver meaningful co-innovation and integrations with complementary technologies. You'll own the technical side of our House Mates partner program and be the person who navigates the multi-org reality of getting an integration certified, listed, and live. This is a hands-on role: you'll write the specs, run the partner calls, drive certification processes, and coordinate across teams to get things over the line.
YOU WILL
- Own the product strategy, roadmap, and execution for ClickHouse's Cloud integrations with strategic partners
- Seek out complementary innovation opportunities with partners. Define what a "better together" integration looks like with each strategic partner, and drive it from joint roadmap through launch.
- Navigate the trade-offs of embedded integrations: billing and metering, identity and auth, security and data residency, and coordination across ClickHouse and partner teams.
- Project-manage complex, multi-org launches: marketplace listings, certification processes, partner co-marketing, and GA timelines across multiple organizations.
- Own the technical standards and certification criteria for integrations submitted through the House Mates partner program.
- Measure and communicate co-innovation business impact, adoption and product strategy to executive leadership.
- Represent ClickHouse externally at partner events and in joint content.
YOU BRING
- Experience shipping integrations into third-party platforms before: hyperscaler marketplaces, embedded or native integrations, ISV partnerships, or OEM/white-label work.
- An understanding of the trade-offs that make or break a partner integration, billing, auth, security, cross-team dependencies, and have made those decisions in the past.
- A strong project management lens and are comfortable owning a launch that depends on five teams across two companies.
- Patience and resilience with partners who are unresponsive or have their own competing priorities, and you find creative ways to keep things moving anyway.
- Technical ability to understand an integration end to end, from provisioning and auth to billing and data flow, and to hold a credible conversation with engineers about APIs, architecture, and technical trade-offs.
- Energy and excitement for external-facing work: partner calls, customer conversations, and representing the product publicly.
- Hands-on and high ownership ability. You write the specs, run the partner calls, and stay close to the details.
- Comfort in ambiguity and fast-moving environments.
PREFERRED QUALIFICATIONS
- Hands-on experience building partner integrations with hyperscalers and modern technology companies.
- Experience running or supporting a technology partner program.
- Background at a database or data infrastructure company; familiarity with ClickHouse or peers like Snowflake, BigQuery, or Databricks.
- Experience working in remote, multi-timezone environments.
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: Remote, Canada; Remote, United States
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.
Co-create the future with us
as we build technology that transforms how the world develops software.
*
Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.
An overview of this role
As Director, Analytics Engineering, you'll lead a team of 8 and report to the VP of Data & Insights. You set direction across the data organization, stay close enough to the work to guide technical decisions credibly, and partner with Data Engineering, Data Science, IT, and business leaders.
You will have three mandates:
Build trusted, AI-ready self-service.
Deliver a semantic model that answers business questions correctly, with the telemetry, evals, and model flexibility to prove it and keep costs in check.
Set the strategy for how GitLab accesses data.
Own the data models, BI tools, and AI access patterns (Claude, MCP servers, Slack agents) that put trusted data in everyone's hands.
Build data applications the whole company relies on.
Ship production-grade apps that combine trusted data, APIs, and AI to answer questions dashboards can't.
What you'll do
Build and own a trusted semantic model, with governed metrics and business definitions, that answers business questions consistently across every tool
Build evals and ground-truth datasets that measure answer quality, and use them to drive improvements and catch regressions
Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they get stuck
Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and quality
Own data modeling and curated datasets for self-service, with the ownership, data contracts, testing, and documentation that make them AI-ready
Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the governance and security to keep access trusted and reliable
Own the enterprise BI and self-service tools strategy (e.g., Tableau, Omni), including evaluation, adoption, and cost
Build self-service capabilities, such as Claude skills, documentation, and guided workflows, that help people find and use data on their own
Build and own company-wide data applications, from Claude-built single-page apps to apps inside BI tools, that combine Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake
Set engineering standards for data apps (security, authentication, testing, deployment, and monitoring) so they're reliable at company scale
Set a long-range roadmap tied to company strategy, and a lightweight operating model that balances urgent stakeholder needs with investment in reusable data products and tech-debt reduction
Hire, coach, and retain a high-performing team of 8: build career paths, develop leaders, distribute ownership, and recognize great work
Act as customer zero for GitLab and GitLab Duo in data workflows, sharing feedback with Product and Engineering
What you'll bring
12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads
Deep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic views, LookML, Cube), and expert dbt, including testing and CI/CD across a multi-team project
Hands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including evals and telemetry for answer quality, and advanced use of AI coding agents such as Claude Code
Expert SQL and strong Snowflake experience; working knowledge of Python
Strong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies)
Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scale
Systems thinker who sees how models, pipelines, and architecture decisions connect, and designs for second-order effects
Exceptional communicator who writes clear technical specs, sets a clear vision, makes trade-offs visible, and influences executives and peers across the company
Pragmatic in ambiguity: makes sound decisions on emerging technology and ships the right next version rather than waiting for the ideal end state
Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values
Nice to Have
Experience with LLM routing or gateway tools and managing model costs
Experience with Tableau, Omni, or a BI platform migration
Experience with web app development (e.g., React, TypeScript) and Postgres
Experience owning finance or revenue-critical data (e.g., ARR, consumption) where accuracy and auditability are non-negotiable
About the Team
Analytics Engineering makes GitLab's data trusted, easy to find, and ready for anyone to use, whether they ask a dashboard, Claude, or a Slack agent. We own the curated data models, the semantic layer, the self-service tools, and the data applications that let teams answer their own questions.
AI is changing how people get to data. Questions that once went through an analyst now go straight to AI tools, so the answers are only as good as the data models and business definitions behind them. Our job is to make those answers correct, consistent, and measurable.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our
benefits
and
equity
. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
United States Salary Range
$139,200
—
$285,600 USD
How GitLab Supports Full-Time Employees
Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and Development Fund
Parental Leave
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from
underrepresented groups
are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines:
GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
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Please review our
Recruitment Privacy Policy.
Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also
GitLab’s EEO Policy
and
EEO is the Law
. If you have a disability or special need that requires
accommodation
, please let us know during the
recruiting process
.
Location: Bengaluru, Karnataka, India, APAC
From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.
About Us
Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data.
Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on.
Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.
As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact.
During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.
About the Role
We’re looking for a Staff Technical Writer to write and edit enterprise documentation that empowers our customers to use Fivetran and understand how our data warehouse, database, and data lake products work. You’ll collaborate with engineers, product managers, support engineers, and other technical writers. You join a friendly team of technical writers distributed among our international offices.
This is a full-time position based out of our Bangalore office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.
Technologies You’ll Use
Documentation-as-code tools, including Markdown, Git, GitHub, and CI/CD workflows
Data platforms such as Snowflake, Databricks, and BigQuery
Cloud storage services such as Amazon S3, ADLS, and GCS
Collaboration and project management tools such as Jira and Slack
What You’ll Do
Create and maintain clear, accurate product documentation and release notes that help customers succeed.
Review and refine customer-facing content, including error messages and UI text.
Use a docs-as-code approach to co-author documentation with engineers, product managers, and contributors across the company.
Improve existing documentation by ensuring technical accuracy, clarity, and consistency.
Collaborate with a global writing team to define and evolve documentation standards, style, and terminology.
Partner with engineers, SMEs, and cross-functional teams to deliver best-in-class technical documentation.
Contribute to style guides, templates, and other shared resources that raise the bar for all company content.
Act as a writing resource for other teams, helping improve content quality across the organization.
Skills We’re Looking For
Extensive expertise in data warehouse and data lake documentation:
8+ years of experience documenting data warehouses, databases, data lakes, and cloud applications for a US-centric audience.
Deep technical knowledge:
Experience with complex data lake and data warehouse technologies, cloud platforms (AWS, Azure, GCP), data pipelines (ETL/ELT), and replication techniques.
Scripting, automation, and AI proficiency:
Skilled at leveraging scripting, automation, and AI tools to streamline documentation workflows and enhance technical content delivery.
Exceptional communication skills
: Proven ability to craft clear, concise, and accurate documentation; strong technical editing abilities; impeccable grammar; and consistent application of style guides.
Documentation leadership:
Expertise in content planning, creation, and review processes, with a track record of implementing best practices that elevate documentation quality.
Project management and organizational skills:
Experience leading documentation projects, mentoring writers, managing competing priorities, and adapting to change while delivering high-quality results.
Collaboration and customer focus:
Strong history of working with engineers, writers, and globally distributed teams, translating customer needs into improved documentation that drives customer success.
Bonus Skills
Experience working at technology companies with globally distributed technical writing teams documenting enterprise-grade products or services.
Understanding of the nuances of complex documentation lifecycles and experience working in an Agile environment.
Experience working in a docs-as-code environment, GitHub, Markdown, CLI, and HTML.
Understanding of cloud object storage, metadata catalogs such as AWS Glue and Unity Catalog, and open table formats such as Apache Iceberg and Delta Lake.
Experience documenting configuration and deployment workflows for containerization and orchestration platforms such as Docker, Podman, and Kubernetes.
#
LI-HYBRID
#LI-DB1
Perks and Benefits
100% employer-paid medical insurance
*
Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off.
RSU stock grants*
Professional development and training opportunities
Company virtual happy hours, free food, and fun team-building activities
Monthly cell phone stipend
Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents.
*
May vary by country and worker type - please reach out to your recruiter for more information
Click
here
to learn more about Fivetran's Benefits by Region.
We’re honored to be
valued at over $5.6 billion
, but more importantly, we’re proud of our
core values of Get Stuck In, Do the Right Thing, and One Team, One Dream
. Read about us in
Forbes
.
Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities.
To learn more about Fivetran’s culture and what it’s like to be part of the team,
click here
and enjoy our video.
To learn more about our candidate privacy policy, you can
read our statement here
.
We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this
form
. We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.
Компания «S7 Techlab» — IT-подразделение крупнейшей частной авиакомпании России. Разрабатывает собственные продукты для продажи авиабилетов, коммуникаций с путешественниками, учета финансов и обслуживания в аэропорту. Системы прогнозируют спрос и управляют предложением услуг, автоматизируют поддержку и улучшают пользовательский опыт на сайте и в приложении S7 Airlines. Программные решения регулируют работу авиапарка, оптимизируют маршруты, оценивают потребности в обслуживании самолетов. Внедряют искусственный интеллект, машинное обучение и облачные технологии, исследуют большие данные и клиентский опыт.
Data office S7 построен на принципах data mesh и децентрализованной аналитики. В линейке продуктов представлены хранилища данных по коммерции, флоту, сотрудникам, пассажирам и рейсам.
Задачи:
— Управление командой разработки в продуктах систем класса DWH: распределение задач, найм, менторинг и развитие подчиненных, контроль и ответственность за результат команды;
— Формирование технических решений;
— Разработка, поддержка и оптимизация ETL процессов для формирования слоя модели данных, витрин данных, а также загрузки данных систем источников;
— Настройка инструментов для обработки и анализа данных;
— Взаимодействие с командой аналитиков по постановке задач и выявлению приоритетов, с командой разработки по технической реализации, со смежными командами (DBA, devops, SRE);
— Миграция с легаси решений на новые целевые.
Требования:
— Опыт от 3-х лет на аналогичной должности;
— Экспертное знание SQL и Python;
— Понимание способов моделирования систем класса DWH и компонентов платформы данных;
— Опыт работы с MPP БД / движками (Vertica, Greenplum, Trino, Spark), глубокое понимание особенностей работы распределенных вычислений;
— Опыт работы с оркестраторами ETL процессов (Airflow, Dagster);
— Опыт управления командой разработки от 2-3 человек.
Будет плюсом, если знаете и применяли в работе:
— Распределенный брокер сообщений Kafka;
— DQ фреймворки (Great Expectations, Soda, Deeque);
— Распределенные объектные хранилища (HDFS, S3);
— SQL фреймворки (dbt, sqlmesh);
— Контейнеризация и оркестрация (Docker, Kubernetes).
Условия:
— Работа в аккредитованной IT-компании;
— Гибридный/офисный формат работы;
— Работа в комфортном офисе по адресу ул. Петровка, 7;
— ДМС со стоматологией после прохождения испытательного срока;
— Корпоративная жизнь с разнообразными коллективными событиями;
— Подарки для детей к первому классу и на Новый год;
— Профессиональное развитие: обучение в компаниях-партнерах, участие и выступление в конференциях;
— Полеты по корпоративным тарифам S7 Airlines;
— Корпоративные скидки в BestBenefits: рестораны, обучающие курсы, товары и т.д.;
— Программа комплексной поддержки «Понимаю» (бесплатные консультации юристов, психологов, нутрициологов, финансистов).
Location: Москва, RU; Россия
О команде
Команда Talent Management Analytics развивает HR-процессы с помощью данных и аналитики. Мы работаем с продуктами целеполагания, Performance Review, Talent Review, обучения и другими HR-сервисами.
Наша задача — помогать бизнесу принимать взвешенные решения: находить закономерности в данных, оценивать эффективность процессов и создавать удобные аналитические инструменты.
Примеры будущих задач:
— собирать, проверять и анализировать данные по запросам бизнеса и продуктовых команд;
— готовить регулярные отчёты, выгрузки и дашборды в BI-инструментах;
— рассчитывать и поддерживать HR- и продуктовые метрики, документировать их логику;
— исследовать изменения показателей, искать причины отклонений и формулировать рекомендации;
— проверять качество данных: полноту, дубликаты, аномалии и соответствие источникам;
— участвовать в развитии витрин данных, аналитических процессов и автоматизации регулярной отчётности;
— помогать коллегам формулировать аналитические задачи и объяснять результаты простым языком;
— принимать участие в подготовке и анализе экспериментов и опросов сотрудников.
Мы ждём, что вы:
— уверенно владеете SQL: умеете работать с JOIN, агрегациями, CTE, оконными функциями и датами;
— хорошо владеете Excel или Google Sheets: используете формулы, сводные таблицы и умеете находить ошибки в данных;
— имеете базовые навыки Python для анализа данных: pandas, NumPy, визуализация данных;
— понимаете основные аналитические метрики: конверсия, доли, динамика, среднее, медиана, удержание;
— знакомы с основами статистики, проверкой гипотез и A/B-тестами;
— умеете работать с BI-инструментами: Redash, Tableau, Power BI, DataLens или аналогами;
— внимательны к деталям, готовы разбираться в бизнес-контексте и задавать уточняющие вопросы;
— умеете ясно рассказывать о результатах анализа.
Будет здорово, если вы:
— работали с ClickHouse, PostgreSQL, Trino или другими аналитическими базами данных;
— имеете опыт в HR- или продуктовой аналитике;
— знакомы с dbt, Git, Airflow или принципами работы DWH;
— строили дашборды и документировали метрики;
— имеете учебные, личные или коммерческие проекты в аналитике.
Работа у нас — это:
— возможность влиять на развитие HR-процессов и HR-продуктов;
— задачи на стыке аналитики, исследований и автоматизации;
— поддержка команды и возможность развиваться в профессии;
— аналитическая культура, инструменты для работы с данными и доступ к обучению;
— возможность работать удалённо или из офиса;
— расширенная забота о здоровье: ДМС, страхование жизни, онкострахование;
— сервис психологической поддержки, а также финансовые, юридические и ЗОЖ-консультации для вас и ваших близких;
— корпоративный спорт: групповые тренировки, велбиинг-приложение;
— спецпредложения от партнёров и скидки на сервисы Авито: бронирование жилья, услуги продвижения, ипотечное страхование;
— компенсация питания.
Location: Worldwide
Workplace: remote
We are looking for a Data Analyst to join our team.Requirements:Solution-oriented mindset;Understanding specifics of iGaming / Fintech;Knowledge of mathematical statistics and hypothesis testing;SQL (complex queries + optimization);Python (general principles + libraries for data analysis);Experience with Airflow, DBT, ClickHouse (DAGs + MVs);Experience with building reports in BI systems.Responsibilities:Solving business problems using data;Collecting and processing data from various sources (ClickHouse, PostgreSQL);Building batch data pipelines using Airflow and DBT;Building core dashboards and models for self service analytics in BI systems (Metabase);Formulating hypotheses and conducting A/B tests with subsequent evaluation of results;Identifying insights and making recommendations for product improvements.We offer:High salary (plus performance bonuses and salary revision);Remote work;Work schedule: Mon-Fri (8 hours per day) with flexible starting hours;24 days holiday leave;Corporate English lessons;Exciting work challenges that allow you to grow to your full potential;A strong team of like-minded professionals who will be by your side to accomplish ambitious projects, stimulate your professional development and bring experience.
УдалённоМожно работать из любой страны
seniorBelgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Monterrey, Mexico; Montevideo, Uruguay; Odesa, Ukraine; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.BG, Bulgaria; Remote.CO, Colombia; Remote.GE, Georgia; Remote.PL, Poland; Riga, Latvia; Rosario, Remote.LATAM-country; Sofia, Bulgaria; Tbilisi, Georgia; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland; Yerevan, Armenia; This position requires availability aligned with the EST time zone or at least a four hour overlap with EST working hours
УдалённоАлматы
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