Дата-инженер вакансии - гибрид

-В первую очередь ищем сильного человека на усиление команды DE, поэтому фокус на разработку и оптимизацию текущих ключевых регламентных процессов. -50% времени - реализация задач по развитию DWH (анализ, разработка объектов DWH, dbt-моделей, потоков данных).

Location: Toronto; San Francisco; Canada; United States; New York; Ottawa; Montreal Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? We’re building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the head of the Data Foundation pillar of our Analytics and Data Insights team, you’ll lead the team that makes Cohere’s data trustworthy, governed, and available: the warehouse every analytics surface runs on, the pipelines that keep it fresh, the access model that keeps it secure, and the agentic analytics layer that lets anyone at Cohere (and their agents) ask questions of governed data directly. Your team owns the full data lifecycle. You’ll run ingestion into BigQuery from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces. Everything is provisioned as code in Terraform, and governance is part of the design: VPC service controls, IAM patterns, and documented access paths that let people and agents move fast without putting data at risk. This role is both highly visible and highly impactful, and you’ll inherit a solid structure on which to build the rest of the stack: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns to keep everything discoverable. The roadmap is set with big bets in flight: scaling that framework across the company, standing up an internal analytics agent with a real eval harness, and consolidating institutional knowledge into a self-correcting and self-maintaining system that keeps context centralized, current, and documented, rather than dispersed and in people’s heads. Responsibilities As the head of the Data Foundation pillar, you will: - Build and lead the team. Hire and grow a team of data and infrastructure engineers; set the technical bar; develop strong talent and raise team performance, building leadership capability beneath you. - Set the roadmap from company strategy. Own and sequence the Data Foundation roadmap: the warehouse buildout, the agentic analytics program, data governance, and the platform work that unblocks our other pillars. You’ll make the trade-offs and carry the cross-functional impact that comes with them. - Own the data platform end to end. Ingestion (managed connectors and an open-source connector framework), orchestration on Airflow and Cloud Run, warehouse modeling in BigQuery with dbt (raw, core, mart layers), and serving through Looker, export APIs, and semantic layers. All of it provisioned as code in Terraform. - Own data governance. Define how humans, service accounts, and agents get access to governed data: VPC service controls, IAM patterns, documented onboarding paths, audit logs, and sensitive requests (including legal holds) handled to deadline. - Operate for reliability. Run the alerting and anomaly-detection framework, own data freshness SLAs, lead incident response and postmortems, and turn every incident into a durable standard so the same class of failure doesn’t recur. - Lead the agentic analytics program. Wire the semantic layer into an internal analytics agent, build the eval harness that measures its accuracy, and make the eval-driven call on where AI earns its way into production. Apply the same discipline to automating data engineering work itself. - Set the standard for analytics across the company. The medallion framework, naming conventions, and testing patterns your team maintains become the way other teams ship analytics data. You’ll onboard new domains onto it and keep the docs accurate to how the systems actually work. - Partner across the org. Work with the North product and engineering teams on the analytics surfaces that ship in the product (including a customer-facing analytics export), with Business Insights on marts for the business, with Security on data governance, and with Legal on compliance-critical data requests. QUALIFICATIONS You may be a good fit, if you have: - 10+ years of experience across data engineering, data infrastructure, or analytics platform work, with a strong management track record leading data platform or infrastructure teams - Serious hands-on history in data engineering or infrastructure before management. You can still read a Terraform plan, a dbt DAG, or an Airflow scheduler log and ask the question that matters - Production experience with cloud data warehouses (BigQuery, Snowflake, or similar), workflow orchestration (Airflow or similar), and infrastructure as code (Terraform or similar) - Depth in data modeling: you think in fact and dimension tables, raw/core/mart separation, and semantic layers, and you have opinions on where tests and contracts belong - A record of setting a team’s roadmap from company or function strategy and delivering outcomes that span teams, with the cross-functional partnerships to match - Operational excellence you can point to: alerting you trust, SLAs you meet, incidents you run to ground and write up so they teach - Exposure to data security and governance: IAM, access management, VPC service controls or equivalent, audit and compliance workflows - Genuine excitement about AI: you follow the research, have opinions, and are energized by building the data foundation an AI company (and its AI agents) runs on - Comfort operating in ambiguity, leading a multi-workstream roadmap, and working directly with executives on priorities If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Vancouver, Canada Workplace: Hybrid Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Who We Are Sensor Tower is the leading solution for mobile marketers, app developers, and industry analysts who demand superior competitive insights into the mobile market economy and are looking to increase app downloads through app store optimization. We serve independent and Fortune 500 customers alike, spanning the mobile games, travel & hospitality, music, finance, and broadcast entertainment markets. Our suite of products consist of free, “SMB”, and Enterprise-tiered solutions including Store Intelligence, Usage Intelligence, Ad Intelligence, and App Intelligence. Our insights are cited by the world’s leading news and finance publications, including the Wall Street Journal, The New York Times, Forbes, Fortune, Bloomberg, CNBC, The Washington Post, and Reuters. Role Summary As Sensor Tower continues to grow as a global company, we are looking for a Senior Data Engineer to build amazing products together. We have a wonderful team of more than a hundred engineers globally and are preparing for much more growth in the coming years. We are looking for an experienced and passionate professional to focus on developing our products in the fast-growing exciting environment. You will report to our Engineering Manager while working closely with the cross-functional product development team and founders. What You’ll Do - Take end-to-end ownership of the data product lifecycle - from business understanding, data analysis, product design, development, deployment, to delivery. - Think beyond coding: bring strong product sense, flexibility in problem-solving, and the ability to proactively align technical solutions with business needs. - Drive communication and coordination across teams to clarify or redefine goals, ensuring data products meet evolving business requirements. - Develop high-quality data programs using PySpark, with strong ownership of data mining and processing challenges. - Conduct code reviews, software design and architecture, and pair programming. - Collaborate closely with product managers and data scientists to design and deliver impactful data products. - Explore and evaluate new technologies in the Data ecosystem, sharing insights with the team. What We’re Looking For - 5+ years experience working on Data Modeling and Data Analysis domain. - Stellar engineering skills with at least 2+ years of experience with most of our core technologies such as: Spark, Python, HDFS, Databricks, AWS, PostgreSQL, MongoDB, and Airflow. - Experience in Pandas, Sklearn or other data science and data analysis toolset is a big plus. - Having a background of data mining and machine learning domain, familiar with common algorithms and libs is a plus. - Solid grasp of modern software development lifecycle. - Ability to efficiently navigate complex multiconstraint decision-making. - Experience working in a diverse and international environment. - Experience in the mobile app, advertising, or gaming ecosystem. - Experience with product design and infrastructure challenges. - Major in Math or Computer Science. Read more about some of our Technical challenges here (written by members of our engineering team): https://sensortower.com/blog/speeding-up-the-backend-with-graph-theory https://sensortower.com/blog/how-we-scaled-to-thousands-of-sidekiq-workers About Sensor Tower Sensor Tower is a global provider of digital intelligence solutions, empowering companies to understand consumer behavior and market performance across mobile apps, digital platforms, and gaming ecosystems. Headquartered in San Francisco, Sensor Tower's insights are trusted by more than 2,500 enterprises worldwide.   Founded in 2013, Sensor Tower’s market insights have helped marketers, app developers, and gaming leaders demystify the mobile app ecosystem with visibility into usage, engagement, and paid acquisition strategies. Today, Sensor Tower’s digital market insights platform has expanded to include Gaming, Web, Audience, and Digital Advertising Insights, helping global leaders understand market trends and their competitor’s strategies and audiences across the entire digital ecosystem.   Why Sensor Tower? Our flexible work environment allows employees to live in greater connection with the people, places, and activities they love! Global Teams Sensor Tower has a global presence, with teams across the world and available in most time zones, including North America, Europe, Middle East, Africa, APAC and LATAM. We maintain regional offices in SF, LA, NY, London, Singapore, Beijing, Seoul, Tokyo and Vancouver.   Our benefits include: - Flexible time off so employees can shape their time away from work. - Health and wellness stipend to achieve and maintain a healthy lifestyle through physical and mental fitness. - Wi-Fi Allowance. - Monthly internet stipend and a one-time $500 home office stipend.   We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, and veteran status. We will consider qualified applicants with arrest and conviction records. If you have a disability or special need, please do not hesitate to let us know and we'll do our best to accommodate. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

• От 7 лет опыта в Python. • Сильный бэкграунд в Data Engineering, построении масштабируемых data pipelines и архитектуре ПО.

-Организация работы команды дата-инженеров: постановка задач, приоритизация, контроль качества выполнения работы. -Непосредственное участие в разработке новых и улучшении текущих дата-процессов.

Разрабатывать и поддерживать ETL/ELT-пайплайны для загрузки и обработки данных из различных источников; Участвовать в миграции существующих процессов загрузки данных на новую data-платформу на базе ClickHouse;

-Анализировать бизнес задачи/проблемы заказчика, транслировать их в аналитические задачи/решения для удовлетворения требований заказчика. -Разрабатывать документы бизнес-требований по шаблону, включая изменения (BRD на CR), определять требования к данным.

Предстоит: Разрабатывать и поддерживать ETL/ELT-пайплайны для загрузки и обработки данных из различных источников; Участвовать в миграции существующих процессов загрузки данных на новую data-платформу на базе ClickHouse;

-разработка и оптимизация ETL/ELT-конвейеров для обработки больших данных. -настройка и администрирование Hadoop/Spark-инфраструктуры (HDFS, YARN, Hive, HBase).

• Коммерческий опыт построения и развития DWH и data pipelines. • Уверенный коммерческий опыт минимум с 3 из 4 инструментов: ClickHouse, Debezium, dbt, Airflow.

Управление командой разработки в продуктах систем класса DWH - распределение задач, найм менторинг и развитие подчиненных, контроль и ответственность за результат команды; Формирование технических решений;

Предстоит: Разрабатывать ETL-процедуры с использованием Python, PySpark, Hadoop, Airflow; Собирать данные из разных реляционных и нереляционных источников (Kafka, Redis, Hadoop);

• 2+ года в Data Engineering / DWH. • Работа с большими объёмами данных.

Не того, у кого Kafka и ClickHouse просто стоят в разделе Skills, а инженера, который действительно работал с DWH, строил ETL/ELT-пайплайны, оптимизировал SQL и понимает, что происходит с данными от источника до витрины. Наш стек: Kafka, ClickHouse, PostgreSQL/MySQL, Airflow, Python/Java/Scala, Docker, Grafana, Prometheus.

Задачи: — построение ETL-процессов: разработка и настройка конвейеров по сбору и трансформации данных из различных источников; — работа с современным стеком трансформации: освоение и применение DBT для превращения «сырых» данных в чистые аналитические витрины; — оркестрация данных: настройка и поддержка рабочих процессов (pipelines) в Dagster для своевременного и безошибочного обновления данных в отчетах; — управление хранилищами: работа с Postgres и высокопроизводительной колончатой базой данных Clickhouse для обеспечения скорости работы отчетов; — визуализация смыслов: разработка интерактивных BI-отчетов в Apache Superset для поддержки бизнес-решений; — оптимизация выборок: анализ и ускорение тяжелых запросов для повышения производительности системы отчетности. Требования: — уверенное владение SQL (сложные выборки, агрегатные функции, оптимизация запросов); — понимание устройства реляционных баз данных, в частности PostgreSQL, и принципов построения аналитических хранилищ; — базовые знания Python, умение писать скрипты для обработки данных и автоматизации простых задач; — аналитический склад ума, способность работать с большими массивами данных, выявлять закономерности и структурировать информацию. Желательный опыт: — опыт создания дашбордов в BI-инструментах (Apache Superset, Tableau, Power BI или аналогичных); — понимание концепций ETL/ELT; — понимание архитектуры данных, разницы между OLTP и OLAP системами (например, использование Clickhouse для аналитики); — интерес к современным инструментам DBT и оркестраторам данных (Airflow, Dagster). Условия: — срочный трудовой договор на 3 месяца; — график 5/2, не более 30 часов в неделю; — возможна удалённая, офисная или гибридная работа; — стажировка доступна студентам любых ВУЗов и форм обучения, включая заочную и магистратуру.

-Разрабатывать и совершенствовать лучшую на рынке платформу данных электронной коммерции нового поколения. -Проектировать и разрабатывать ETL пайплайны на Airflow для Spark (Batch, Streaming), Iceberg, Trino.

Задачи: — построение ETL-процессов: разработка и настройка конвейеров по сбору и трансформации данных из различных источников; — работа с современным стеком трансформации: освоение и применение DBT для превращения «сырых» данных в чистые аналитические витрины; — оркестрация данных: настройка и поддержка рабочих процессов (pipelines) в Dagster для своевременного и безошибочного обновления данных в отчетах; — управление хранилищами: работа с Postgres и высокопроизводительной колончатой базой данных Clickhouse для обеспечения скорости работы отчетов; — визуализация смыслов: разработка интерактивных BI-отчетов в Apache Superset для поддержки принятия бизнес-решений; — оптимизация выборок: анализ и ускорение тяжелых запросов для повышения производительности системы отчетности. Требования: — уверенное владение SQL (сложные выборки, агрегатные функции, оптимизация запросов); — понимание устройства реляционных баз данных, в частности PostgreSQL, и принципов построения аналитических хранилищ; — базовые знания Python, умение писать скрипты для обработки данных и автоматизации простых задач; — аналитический склад ума, способность работать с большими массивами данных, выявлять закономерности и структурировать информацию. Желательный опыт: — создание дашбордов в BI-инструментах (Apache Superset, Tableau, Power BI или аналогичных); — понимание концепций ETL/ELT; — понимание архитектуры данных, разницы между OLTP и OLAP системами (например, использование Clickhouse для аналитики); — интерес к современным инструментам DBT и оркестраторам данных (Airflow, Dagster). Условия: — срочный трудовой договор на 3 месяца; — график 5/2, не более 30 часов в неделю; — возможность работы удаленно, в офисе или в гибридном формате; — стажировка открыта для студентов любых ВУЗов и форм обучения, включая заочную и магистратуру.

Эксплуатация и тюнинг СУБД: Полный контроль над состоянием, профилированием и оптимизацией PostgreSQL под конфигурацию серверов в AWS; Отказоустойчивость и HA/DR: Настройка и сопровождение репликации, Patroni, PgBouncer, бэкапирования и катастрофоустойчивости;