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Location: Malta The Wow This role sits at the heart of our real-time data platform, empowering teams to build, deploy, and scale data products that drive critical business decisions and customer experiences. You will design, develop, and operate the core platform capabilities that power streaming data pipelines, event-driven applications, and self-service data products. Working at the intersection of software engineering and data engineering, you will create scalable frameworks, tooling, and developer experiences that enable our teams to deliver reliable solutions with speed and confidence. A taster of what you will be involved with: Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing. Develop and maintain the platform's core capabilities, such as orchestration, data quality validation, and schema management tools. Evolve the platform's architecture to incorporate new technologies that improve scalability, reliability, and cost-effectiveness. Collaborate with Data DevOps Engineers to ensure platform features are automated, observable, and deployed via CI/CD. Act as a key contributor to the platform's roadmap, identifying and prioritizing features that unlock the most value for its users. What we are looking for: Must haves: University Degree in Computer Science, Engineering or equivalent. At least 3 years of hands-on experience building and operating real-time or event-driven data platforms and streaming applications. Strong software engineering fundamentals, with experience in a language like Python, Scala or Java. Experience building reusable frameworks, libraries, or internal tools. Deep knowledge of SQL and data integration patterns. Experience in modern cloud database technologies such as Snowflake or Redshift are considered an asset. Experience with data streaming technologies such as Kafka is a must. Strong experience building distributed data processing workloads using Apache Spark (PySpark and/or Scala). Hands-on experience designing and operating event-driven architectures on AWS, including services such as MSK, Kinesis Data Streams, EKS, EMR, Lambda, and EventBridge. Experience in NoSQL databases such as  HBase, Cassandra, and DynamoDB. Excellent verbal and writing English communication skills. Nice to have: Familiarity with real time reporting tools like Grafana or Datadog Familiarity with Data Modelling Concepts like Inmon, Kimball and Data Vault Knowledge AWS services like Glue, Lambda, Step Functions and S3 Experience with orchestrating data pipelines using tools like Airflow. Experience building or managing APIs and microservices. Familiarity with infrastructure scripting like Terraform and CI/CD practices. What we offer Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in. Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Задачи: - Разработка Python-сервисов для аналитики, расчета себестоимости, цен и скидок. - Создание и поддержка API-интеграций с 1С, сайтом, маркетплейсами и внешними системами. - Разработка ETL-процессов и обработка больших объемов данных. - Проектирование и оптимизация запросов в ClickHouse и PostgreSQL. - Настройка асинхронной обработки задач (Celery, RabbitMQ/Kafka). - Создание аналитических дашбордов и отчетности. - Рефакторинг существующих сервисов, код-ревью и повышение качества кода. Требования: - Python от 4 лет в коммерческой разработке. - Опыт работы с Celery и RabbitMQ/Kafka. - Опыт построения ETL-пайплайнов и работы с большими данными. - Уверенный SQL, ClickHouse и PostgreSQL. - Опыт с Airflow или Dagster. - Docker, Kubernetes. - Опыт разработки и поддержки REST API. - Понимание форматов JSON/XML и интеграционных процессов. - Опыт использования AI-инструментов для ускорения рутинных задач, грамотный промпт-инжиниринг и строгое ревью сгенерированного кода. Будет плюсом: - Go. - Apache Superset. - Интеграции с 1С. - Опыт в e-commerce/ритейле, понимание FIFO и расчета себестоимости. - Интеграции с Честным ЗНАКом и ЕГАИС. Условия: - Официальное трудоустройство по ТК РФ и полный социальный пакет. - График работы: 5/2 с 9:00 до 18:00 (сб, вс - выходные). - Корпоративные скидки на автозапчасти для сотрудников. - Материальная помощь по семейным обстоятельствам. - Бесплатные комплексные обеды за счет компании. - Доставка к месту работы служебным транспортом. - На территории имеется парковка и зоны отдыха. - Корпоративная культура: занятия спортом, реферальная программа, мероприятия, новогодние праздники, обучение и повышение квалификации, оплачиваемые курсы.

Задачи: - Разработка микросервисов управления данными Модели Космической Системы; - Разработка пайплайнов обработки данных ETL/ELT; - Интеграция вычислительных модулей (микросервисов); - Реализация процессов контроля качества данных; - Разработка моделей данных и согласование дата-контрактов; - Работа с СУБД Postgres, Clickhouse; - Обработка и анализ данных в Pandas, NumPy, Polars. Стек разработки: Python 3.12+, FastApi (Pydantic v2), Numba, Numpy, Pandas, SQLAlchemy 2+, Ruff+MyPy (lint), Kafka (FastStream), Redis (Dragonfly), Matlab, Postgres, Clickhouse. Требования: - Инженерное или техническое образование (обязательно); - Опыт разработки на Python от 3х лет, на позиции Middle - от 1 года; - Опыт работы с библиотеками для анализа данных: Pandas, NumPy, Polars; - Понимание принципов проектирования и работы с хранилищами данных; - Опыт работы с базами данных PostgreSQL, ClickHouse; - Опыт работы с инструментами ETL/ELT (например, Airflow, Dagster, PandasETL); - Понимание принципов работы систем потоковой обработки данных; - Опыт в разработке веб-приложений (FastAPI); - Опыт работы с контейнерами Docker; - Опыт работы с инструментами командной разработки: Confluence, Jira, Git. Условия: - Работа в аккредитованной ИТ-компании; - Возможность выбора формата работы (офис/гибрид); - Комфортный современный офис (м. Мнёвники); - Оформление в соответствии с ТК РФ; - Конкурентный уровень заработной платы - на уровне лидеров ИТ/телеком-индустрии.

Чего ждём от тебя Без этого не получится: - 5+ лет в ML/DS — опыт выкатывания моделей в прод и понимание практических аспектов - Уверенный Python: ООП, типизация, тесты - Классический ML: бустинги, валидация, понимание, где нейросеть избыточна, а где достаточно градиентного бустинга - Опыт с текстовыми нейросетевыми моделями: BERT-подобные трансформеры, LLM API, промпт-инжиниринг, eval-сеты - Практический опыт MLOps: пайплайны данных, оркестрация (Airflow, Kubeflow или аналоги), трекинг экспериментов - Инфраструктурный бэкграунд: Docker, CI/CD, Kubernetes, логирование и мониторинг — понимание высоконагруженных сервисов - Умение мыслить P&L: перевод метрик моделей (F1, ROC-AUC) в конверсии и деньги, защита технических решений перед бизнесом финансовыми аргументами - Опыт менторства или лидерства и желание этим заниматься

Задачи: - Реализация высоконагруженных конвейеров обработки данных для обеспечения надежной и бесперебойной репликации данных из ИТ-систем Банка. - Реализация комплексных задач по подготовке данных в целевых аналитических хранилищах (DataLake, SandBox, FeatureStore) для построения признаков, необходимых для разработки моделей машинного обучения. - Разработка и поддержание в актуальном состоянии документации по разработанному функционалу. - Своевременное отражение статуса выполнения задач в Jira. - Проверка качества кода (код-ревью), написанного инженерами и младшими инженерами данных. Требования: - Python - уверенное знание структур данных и алгоритмов, эффективное применение принципов ООП и ФП (Функциональное программирование), опыт написания модульных и интеграционных тестов, знание и опыт применения библиотек обработки и анализа данных - numpy, pandas. - Опыт разработки и внедрения в промышленную эксплуатацию сервисов загрузки и обработки неструктурированных и слабо структурированных данных (текст, xml, json) из внешних источников. - Способность разобраться с API поставщиков данных, используя доступную документацию. - SQL - умение создавать сложные запросы с использованием аналитических оконных функций и использовать инструменты профилирования для оптимизации их производительности, опыт работы с БД Oracle, Postgres, Greenplum. - Уверенное знание и опыт работы с инструментами разработки, планирования и мониторинга рабочих процессов (workflow engines) пакетной обработки данных. - Airflow. - Опыт разработки сложных, высоконагруженных приложений обработки данных на основе PySpark, уверенное знание настроек Spark и их влияния на производительность приложений Spark.

Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role The Aidoc Clinical Value team plays a pivotal role in evaluating the outputs and performance of Aidoc's products to demonstrate the value delivered to customers in real-world clinical and operational settings. We are looking for an experienced Analytics Engineer to join our Clinical Value team and develop the data foundations, infrastructure, and analytical tools that enable our work. This hybrid role combines Analytics Engineering with hands-on data analysis. You will translate complex analytical and clinical needs into scalable, reliable, and reusable data solutions. You will design data models, pipelines, analytical layers, and tools that enable complex Clinical Value studies across products and customers, while remaining hands-on with selected analytical projects. You are expected to be independent, proactive, and impact-oriented, taking end-to-end ownership of technical challenges and opportunities for improvement. evaluation. Responsibilities Design, build, and maintain the data infrastructure supporting Clinical Value analyses , including reusable data models, pipelines, analytical layers, and tools. Own the technical and analytical implementation of complex Clinical Value applications , adapting established methodologies to different products, customers, and real-world data environments. Develop complex analytical solutions into reusable and scalable frameworks , enabling broader and more efficient execution across the team. Identify data-quality issues, technical bottlenecks, and repetitive processes, and develop solutions and automation to improve reliability and efficiency. Work closely with analysts, Data Engineering, and other technical teams to translate analytical needs into effective, maintainable data solutions and establish best practices. Lead selected hands-on data-analysis projects , analyzing complex clinical and operational datasets to generate credible, actionable conclusions. Collaborate with Go-to-Market teams, including Customer Success, to understand customer needs and support impactful customer-facing value demonstrations. Requirements Education & Experience: B.Sc. or higher in a Scientific or Engineering discipline with 5+ years of experience in Analytics Engineering, Data Engineering, or a technical analytics role . Core Technical Stack: Advanced Python and SQL skills; hands-on experience designing and building production data models, pipelines, and analytical layers. Tools & Platforms: Experience with orchestration/transformation tools (DBT, Airflow, or similar) and cloud data platforms (Databricks, Snowflake, BigQuery, or AWS). Engineering Standards: Strong understanding of data modeling, data quality, testing, and maintainability best practices. AI Tooling & Automation: Hands-on experience integrating AI development tools and agents (e.g., Cursor, Claude agents, GitHub Copilot) into daily workflows to accelerate coding, debugging, and pipeline development. Data Analysis Capabilities: Strong analytical mindset with the ability to independently explore and analyze complex datasets, summarize findings, and extract meaningful insights as needed. Problem-Solving & Communication: Demonstrated ability to work independently, manage tight timelines, and translate ambiguous analytical needs into robust technical frameworks. Excellent communication skills for bridging technical and non-technical stakeholders. Nice to have Prior experience or a strong passion for healthcare, AI, or the medical field. Proven experience in project management or technical team leadership. Working at Aidoc Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Обязанности: • Участвовать в разработке ИИ-агента • Взаимодействовать в составе команды со специалистами по анализу данных и специалистами по развитию инфраструктуры • Проводить функциональное тестирование • Работать в Jira и Confluence Требования: • Понимание общих принципов реляционных баз данных (таблица данных, первичный и внешний ключи, индексы, связи между таблицами) • Продвинутое знание MS Excel, SQL, Python • Наличие представления об основных банковских продуктах • Наличие интереса к искусственному интеллекту и желание использовать его в личных и стратегических задачах • Будет преимуществом базовое знание системы оркестрации процессов обработки данных Apache Airflow и базовое знание инструментов визуализации Apache Superset

Location: Chicago DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. UP (Unified Platform) consolidates data and technologies into a comprehensive solution, accelerating time to market. Optimizing decision-making and research, our platform simplifies implementing new ideas, enhancing our competitive edge. We work from high-level requirements where programmers are expected to gain an intimate understanding of the business. We strive for an environment where developers have the autonomy to pursue business solutions without arbitrary management constraints. We are a group of polyglots and technologists always seeking to find the right tool for each problem. Broadly, the development teams at DRW believe in rapid deployment and feedback, automated testing, and cohesive, transparent, lightly coupled service architectures. DRW has openings for Senior Software Engineers on its Treasury and Reference Data development teams. These teams build and operate systems the firm depends on for financing, liquidity, and the instrument data that underpins trading and post-trade workflows. The teams are small and collaborative — you’ll work directly with business partners and enjoy building meaningful products from day one. These openings sit on two related teams: Treasury — builds systems that support position financing, margin and collateral management, and cash and liquidity management across the firm. Reference Data — owns the data platform that stores and distributes instrument and related reference data used across research, trading, and post-trade workflows. We hire through a single interview pipeline and match candidates to the team and problems that fit best as we learn more about each person’s current skills and long-term development goals. Responsibilities: Designing, building, and testing systems used across the firm — services, data products, and the UIs that sit on them Collaborating with business partners to turn ambiguous business problems into clear technical plans and shipped software Owning software end-to-end after it ships — we run what we build (deploy, operate, on-call) Working across greenfield systems and existing codebases Building and improving tooling and processes around CI/CD, containers, and Kubernetes / internal cloud Mentoring and raising the bar for engineering practice Learning and championing useful new technologies where they fit Desirable Experience: We are looking for strong senior generalists. Experience in the following areas is helpful: Full-stack development in Java, Python (FastAPI), and/or Ruby (Rails) Strong relational data modeling fundamentals GitOps and Kubernetes Job orchestration systems (Airflow, Prefect, etc.) Though prior domain experience is not required, relevant background can help place a candidate on a particular team: Payments and/or treasury systems (Treasury) Vendor/exchange data processing and/or data taxonomy (Reference Data) The annual base salary range for this position is $200,000 to $275,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-GV1

Location: London DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. DRW has an opening for a Senior Software Engineer focused on digital assets. The team builds and operates systems that move and safeguard cryptoassets across the firm — including treasury automation, wallet inventory and reference data, integrations with custody platforms, and operational controls used by digital asset operations. You’ll work directly with those business partners and enjoy building meaningful products from day one. At DRW we strive for an environment where technologists are free to pursue solutions to the problems of the business free from arbitrary management constraints and supported by excellent technical resources. All development teams at DRW believe in rapid deployment and feedback, automated testing, and cohesive, transparent, lightly-coupled service architectures. We ship on Kubernetes with modern CI/CD. Candidates should have strong initiative and proven experience independently driving projects to completion. We work from high-level requirements and value engineers who dig into the business to build the right thing. Responsibilities: - Designing, building, and testing full-stack applications (APIs through UI) used by digital asset operations and related business partners - Partnering with those teams to turn ambiguous business problems into clear technical plans and shipped software - Owning software end-to-end after it ships — we run what we build (deploy, operate, on-call); we don’t hand systems off to a separate ops team - Working across greenfield systems and existing codebases - Building and improving tooling and processes around CI/CD, containers, and Kubernetes / internal cloud - Collaborating with other software teams, trading desks, and business units - Mentoring and raising the bar for engineering practice on a small team - Learning and championing useful new technologies where they fit Desirable Experience: - We are looking for strong senior engineers with crypto or digital-asset systems experience. Deep Python expertise is a meaningful differentiator for this role. - Cryptoassets, digital-asset operations, or custody / wallet platforms (or closely adjacent high-stakes money-movement systems) - DeFi, smart contracts, staking, or other on-chain systems - Full-stack development with Python (FastAPI) - Strong relational data modeling fundamentals - GitOps and Kubernetes - Job orchestration systems (Airflow, Prefect, etc.) For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-MM1

Location: Warsaw The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call. As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday, with the option to work from home on Wednesdays and, depending on the work and the teams you partner with, on Fridays. If you're interviewing for this role, your recruiter will share more about the in-office expectations. What you'll achieve: Own the Gold layer for a given business domain (e.g. PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, and where to find it. Partner with peers across DS&A to keep KPI definitions consistent where domains overlap. Author data contracts and SLAs at the Silver→Gold boundary, partnering with Horizontal Data Engineering on the inputs you depend on, and owning data quality, freshness, and oncall for Gold/metric-mart failures in your domain. Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products rather than one-off builds. Partner directly with Product & Business, Data Science, and Engineering to turn ambiguous, underspecified questions into scalable datasets — anticipating downstream reporting impacts before they become incidents, and raising the data-model quality bar across the domains you touch. About you: 4+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions. Advanced SQL and strong data modeling fundamentals: dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design. Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred). Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning. Demonstrated domain fluency in at least one business area (e.g. PLG funnels, SLG pipeline, marketing attribution, Product telemetry, revenue/ARR) and the judgment to translate "I don't trust this number" into a specific, durable model fix. Strong cross-functional partnership skills: requirement gathering, prioritization, documentation and enablement, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical partners. Curiosity about AI-native analytics — NL2SQL, metadata/semantic layers for self-serve, and using tools like Claude and Genie to multiply your reach rather than replace rigor. Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation (Salesforce, Marketo, Gainsight) is a plus. We know that the best ideas and solutions come from multi-dimensional teams. That's because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don't be shy - apply today. At Asana , we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Generous, transparent and fair compensation system (base salary and RSUs) Contract of Employment (and the option of 50% tax deductible costs for author’s rights usage in respect of applicable roles ) Health insurance with dental and travel coverage (Lux Med) Breakfast and lunch catering on the days that you work from the office Vacation allowance Career growth budget Home office setup budget Gym/Fitness card Fertility healthcare and family-forming support with Carrot Mental Health Support in Modern Health Group life insurance MacBooks with all necessary accessories For this role, the estimated base salary range is between 20,833 - 23,700 PLN gross per month (subject to all taxes and necessary deductions). The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity and sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. #LI-Hybrid About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. Join Asana ’s Talent Network to stay up to date on job opportunities and life at Asana . About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to 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 law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Barcelona, Spain Workplace: hybrid About seQura seQura provides innovative, flexible and easy-to-use payment technologies that help merchants acquire, convert and retain more customers. We make a difference in sales performance by tailoring our solutions to different sectors, to address their unique pain points and deliver superior results in Retail, Education, Eyewear, Repairs and Travel. We also empower smart shopping to consumers who seek more value, convenience, and flexibility in their shopping, with new payment experiences that allow them to save, access interest-free credit, or pay in small, comfortable installments of up to 24 months. Born in Barcelona, seQura is a privately-owned fintech, currently expanding throughout southern Europe and Latin America, growing above 50% CAGR. Over 6000 businesses, almost 3 million shoppers, and almost 400 employees continue to rate us as one of the most loved and trusted fintechs out there, with an NPS of 87%, a Trustpilot rating of 4.7/5, and a Glassdoor rating of 4.1/5. About the role 🤓 Finance at seQura runs on data: recurring calculations, regulatory processes, provisioning, reporting cycles, and profitability tracking. As a Senior Financial Product Data Analyst, you'll own the link between how Finance actually works, the KPIs it tracks, and the decisions those KPIs drive, turning that understanding into reliable, self-service data products. This isn't a "receive a ticket, write a query" role. You'll work closely with Finance and Finance Tech teams to understand why a number matters before you model it, then build trusted data products that Finance teams can use independently. Your work will directly improve how Finance operates, helping establish a single source of truth for revenue, enabling self-service reporting, and ensuring the business can make confident decisions based on reliable data. What challenges you'll be solving 🚀 Learn seQura's Finance domain deeply enough to understand which KPIs matter, why they matter, and the business decisions they support—from pricing and provisioning to servicer settlement and product profitability. Design and build production-grade data products, not just queries: dbt models on Redshift, fully documented and tested to Single Source of Truth standards, together with the Metabase dashboards and self-service datasets that sit on top of them. Partner directly with Finance stakeholders to translate complex financial and regulatory processes into robust, reliable, and auditable data models. Validate and reconcile critical Finance outputs, including servicer reports, provisioning runs, and amortisation tables, ensuring they are accurate and audit-ready. Chase data quality issues back to their source, working closely with Data Engineering to solve problems upstream instead of applying downstream workarounds. Help close the existing revenue gap between operational systems and the data warehouse while improving Finance models for defaults and amortisation. Present findings, recommendations, and new data products directly to Finance leadership, connecting the data back to the business decisions it's meant to support. Contribute to broader Data & AI governance initiatives, including metadata, documentation, and data catalog work wherever it impacts Finance. About the Data team 🧩 Team mission To turn seQura's raw data into trusted, well-governed data products that power business decisions, reporting, and AI across all domains. What we own The dbt transformation layer across business domains. The Single Source of Truth (SSOT) for key business metrics. Semantic models that enable consistent reporting and analytics. Data contracts and governance standards across domains. Data lineage, documentation, and discoverability. Data quality, testing, and monitoring to ensure trusted data products. Team Structure You'll join a team of four Analytics Engineers, working alongside a Data Governance Lead and reporting to the Head of Data. You'll collaborate closely with FP&A, Accounting, Treasury, Finance Tech, Data Engineering, and the wider Data & AI team to ensure Finance data is accurate, governed, and easy to consume. How we work We treat data as a product, with clear ownership, quality standards, and consumers. We build self-service data products rather than one-off reports. We understand the business context before building data models—we care as much about why a metric exists as how it's calculated. We work closely with domain experts to turn business knowledge into reusable, trusted data assets. We continuously improve data quality through governance, documentation, testing, and collaboration. What to expect in the next 90 days 🏁 Month 1 Learn seQura's core Finance processes and KPIs, including pricing, provisioning, servicer settlement, and product profitability. Meet stakeholders across Finance and Finance Tech, and become familiar with the existing dbt models and Metabase dashboards supporting Finance. Month 2 Take ownership of your first data quality or reconciliation initiative end-to-end, tracing issues back to their source alongside Data Engineering while contributing to an active dbt model. Month 3 Deliver your first self-service Finance data product—a documented dbt model together with a Metabase dashboard—that Finance stakeholders can use independently, and present your work and recommendations to Finance leadership. Tech stack & environment 🛠️ Our Finance Analytics stack is built around SQL, dbt, Redshift, and Metabase, enabling trusted, production-grade data products across Finance. The team uses dbt for transformation and testing, Redshift as the analytical warehouse, and Metabase to deliver self-service reporting. OpenMetadata supports governance and discoverability, while Python and Airflow are used where automation or orchestration adds value. What you’ll need 🤝 Must have: 5+ years of experience as a Data Analyst or Analytics Engineer. Strong hands-on SQL skills. Practical experience with dbt, including data modeling, testing, and documentation. Experience building dashboards and self-service data products using Metabase (or an equivalent BI platform). Demonstrated ability to understand Finance processes, not just execute against a specification, and translate that understanding into robust data logic. Strong business mindset, with the ability to connect KPIs to the decisions they support. Fluent English. Nice to have: Experience in fintech, lending, or BNPL environments. Knowledge of provisioning, amortisation, EIR, or IFRS 9. Python for analysis or lightweight automation. Experience with data governance or catalog tools such as OpenMetadata. Experience with orchestration tools such as Airflow. Experience presenting data products directly to Finance or executive stakeholders. What we offer 😎 We have a strong and sustainable foundation, where we provide a secure and reliable workplace. You have the freedom and trust to make the best contribution possible. One of our most valued strengths by our employees is our fellowship and supportive culture, which fosters a sense of belonging by working closely with our values. With us, you will have challenging projects to work on and push your skills and knowledge. In addition, we are very proud of the unique office we have, which offers a comfortable and inspiring environment to work in with everything you need. 23 vacation days + 2 days of free disposal per year. Flexible compensation plan for transportation, restaurants, and kindergarten with Cobee. Health insurance discounts Flexible working hours. A personal budget for professional development. Office workshops and meet-ups to encourage community participation and career growth. Hybrid work from Barcelona Moreover, we have a Wellness Program that embraces a holistic approach by covering 6 areas (occupational, physical, financial, emotional, social, and environmental consciousness). Each area will include a variety of activities, and you'll be able to choose from 34 different activities that best meet your needs to configure a plan that best works for you. Which are the next steps? 🙌 Interview with People Team Hiring Manager interview Technical take-home assessment (async) Live Peer review of the assessment Meet the team We kindly ask that you submit your CV in English, as it is the official language of our community. We promote equal opportunity to all, regardless of age, color, gender identity, medical condition, physical or mental disability, race, religion, sexual orientation, or any other characteristic. We have an inclusive environment, and respect is above all. Do you want to be part of the change? Join us!👇

Задачи: - Внедрять AI-инструменты, агентов и сценарных ботов в продукты и сервисы. - Разрабатывать микросервисы для обработки данных. - Проектировать и оптимизировать ETL-процессы. - Поддерживать и развивать потоковые и пакетные системы обработки данных. - Повышать производительность, отказоустойчивость и масштабируемость существующих решений. - Интегрировать различные системы и источники данных. - Автоматизировать мониторинг и систему алертинга. Требования: - Опыт работы с данными и их трансформацией с использованием SQL (ClickHouse, PostgreSQL, Vertica, Trino и другие). - Уверенное знание Python. - Опыт работы с инструментами оркестрации процессов (Airflow). - Понимание архитектуры и принципов построения ETL-пайплайнов

Workplace: remote Requirements 2+ years with Python including strong knowledge of data libraries (pandas, multiprocess, Google Cloud SDK) 2+ years of experience in ETL/ELT technologies (REST API, GraphQL, DBT, etc. ) and data pipeline orchestration (e.g., Airflow, Astronomer, DBT cloud, etc) Hands-on experience with Snowflake Problem-solving and root cause analysis in live production systems along with experience querying and transforming large volumes of data, data quality and data validation Experience in SQL (SQL Server, Oracle, MySQL, BigQuery, Snowflake) Comfortable working with serialized data format (JSON, AVRO, XML, CSV) as well as compressed and encoded files Comfortable with ingesting data using REST APIs, data transformations and data loading/unloading techniques English proficiency sufficient to work in an international environment Nice to have Capable of designing and implementing data pipelines over cloud architecture Experience working with CI/CD deployments Experience working with GIT We offer Projects for such clients as PayPal, Wargaming, Xerox, Philips, adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely Corporate medical insurance covering services of private and public medical centers English courses online Corporate parties and events for employees and their children Gym membership compensation, corporate sport competitions (cybersport included) 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate Any questions? Anna hh@itransition.com

Location: Los Angeles, USA Riot’s Data Engineers harness petabytes of data and state-of-the-art processing technologies to build products that elevate the player experience at massive scale. Turning this data into meaningful insights is a complex challenge, and our engineers meet it by staying deeply player-focused and collaborating across diverse teams to improve the lives of millions of players worldwide. As a Principal Data Engineer supporting Riot’s Central Product Insights, you will design, build, and maintain scalable data pipelines and models that power critical data products, including centralized player data models, and publishing activity data systems. These systems support understanding of player onboarding funnels, engagement patterns, support efficiency, and content effectiveness. You will collaborate with product managers, analysts, and engineers to ensure our data infrastructure is reliable, performant, and directly tied to delivering better player experiences. Responsibilities: Design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights use cases, growth metrics, and other publishing/marketing focused data sets. Design and implement data models using industry best practices that capture a complete ecosystem view of in- and out-of-game experiences, while ensuring accuracy, scalability, and long-term usability. Architect and implement robust, maintainable, and high-performance data solutions. Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for content, growth, and pubsports areas of coverage. Mentor data engineers across all levels, setting best practices and fostering technical growth. Optimize query performance and resolve pipeline bottlenecks to improve data accessibility. Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities. Support cost optimization by ensuring scalable and efficient data solutions. Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA). Contribute to Riot’s Data Engineering discipline shaping infrastructure, craft standards, tooling, and organizational best practices Required Qualifications: Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. 8+ years experience in tech-focused Publishing or Marketing fields. 8+ years experience in data engineering or a related field. Strong Expertise in big-data technologies, including Python, GoLang, Spark, Scala, SQL, and tools like Airflow and dbt. Proficiency in cloud infrastructure (AWS or GCP) and Databricks. Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders. Demonstrated ability to work cross-functionally with engineering, analytics, and product teams. Proven experience mentoring and guiding other engineers. Desired Qualifications: Experience in gaming, large consumer platforms, or systems leading data modernization or transformation initiatives in a complex environment Track record improving data maturity ( e.g. SLI’s/SLO governance, reliability standards) Experience designing semantic layers or standardized business metric frameworks Background supporting advanced analytics use cases in high velocity product environments Demonstrated ability to influence standards across teams in a matrixed organization For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position! 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.

Задачи: - разрабатывать и поддерживать DAG в Apache Airflow - работать со скорингом (рассчитывать стратегии взыскания клиентов) - программировать на Python (основном языке) - оптимизировать запросы и работать с Oracle (SQL, хранимыми процедурами) - поддерживать и сопровождать выгруженные DAG - участвовать в разработке и применении моделей (машинном обучении, сегментации клиентов) - проводить код-ревью - самостоятельно проводить аналитику (в команде нет системных аналитиков) Требования: - python – уверенное коммерческое программирование - Airflow – создание DAG, опыт работы - Oracle – SQL на уровне оптимизации запросов, хранимые процедуры - Linux – базовые навыки (собрать образ, решить задачу без DevOps) - Kubernetes – опыт работы (упоминался) - Middle: ~2–3 года коммерческой разработки на Python - релевантный опыт с Airflow – желательно 2–3 года - опыт именно оптимизации запросов в Oracle, а не просто написания простых запросов

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: As a Data Scientist, you will help measure the impact of PlayStation's products, features and commercial initiatives through experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will apply robust analytical techniques to solve complex business problems, generate actionable insights and support evidence-based decision-making across PlayStation. This role goes beyond traditional A/B testing. You will apply modern causal inference, statistical modelling and machine learning techniques to evaluate initiatives where controlled experiments are difficult or impossible, collaborating closely with product, engineering, analytics and business teams to deliver high-quality measurement and insights. This is an opportunity to work on high-impact initiatives affecting millions of PlayStation players while developing your expertise in experimentation, causal inference and applied data science. What You'll Be Doing: Apply measurement methodologies across experimentation, causal inference and advanced analytics to evaluate product and commercial initiatives. Design and execute robust measurement approaches across randomised experiments, quasi-experimental methods and observational causal inference where controlled experimentation is impractical. Apply statistical, machine learning and AI techniques to solve complex measurement challenges and generate actionable business insights. Apply advanced data science and machine learning techniques where appropriate to complement experimentation and support complex business decisions. Contribute to the development and adoption of best practices for experiment design, statistical analysis and causal measurement. Partner closely with product managers, engineers, analysts and business stakeholders to identify high-impact measurement opportunities and ensure product and commercial decisions are supported by rigorous evidence. Collaborate with engineering teams by providing feedback on experimentation and measurement capabilities to improve tooling and workflows. Develop reusable analytical solutions, dashboards and code that improve the quality, consistency and efficiency of measurement. Communicate analytical findings and recommendations clearly to technical and non-technical stakeholders. Stay current with emerging developments in statistics, machine learning and AI, identifying opportunities to improve measurement capabilities and analytical workflows. Contribute to a culture of evidence-based decision-making by sharing knowledge, collaborating across teams and promoting analytical best practices. What We're Looking For: Required: Master's degree (or equivalent industry experience) in Statistics, Economics, Mathematics, Computer Science, Data Science or another quantitative discipline. PhD preferred. 3+ years of industry experience applying experimentation, causal inference, statistical modelling, machine learning or related analytical techniques to solve business problems. Good understanding of experimental design, A/B testing and modern causal inference methods, including quasi-experimental approaches. Experience applying data science, machine learning and statistical modelling techniques to analyse complex datasets and generate actionable insights. Strong proficiency in Python and SQL for analytical workflows. Experience developing robust analytical solutions using sound statistical principles and software engineering best practices. Strong stakeholder management and communication skills, with the ability to explain technical concepts clearly to both technical and non-technical audiences. Curiosity, creativity and a pragmatic approach to solving ambiguous business problems. A collaborative mindset with a passion for continuous learning and improving analytical capabilities. Preferred: Experience working in gaming, digital products, consumer technology, e-commerce or subscription businesses. Familiarity with modern data engineering and analytics tooling such as Databricks, Snowflake, Git and Airflow. Experience with modern business intelligence and data visualisation tools such as Tableau, Domo or Power BI. Experience applying AI tools, including large language models (LLMs), to improve data science workflows and analytical productivity. Experience developing reusable analytical frameworks, libraries or internal tooling. Experience presenting analytical findings and recommendations to cross-functional stakeholders. What You'll Influence: Measurement for PlayStation's product and commercial initiatives. High-quality experimentation and causal inference across product and business teams. Product and commercial decisions through rigorous analytical evidence. The continued evolution of PlayStation's measurement and experimentation capabilities. Why You'll Love This Role: Help shape how PlayStation measures product and commercial success across a global business. Work on challenging real-world problems using experimentation, causal inference and machine learning. Collaborate with talented scientists, engineers and product teams on high-impact initiatives. Learn from experienced data scientists while developing your expertise in modern measurement and experimentation. Contribute to the adoption of evidence-based decision-making across PlayStation. Continue growing your technical and business skills in a collaborative, supportive environment. Benefits: Discretionary bonus opportunity Hybrid Working (FlexModes) Private Medical Insurance Dental Scheme 25 days annual leave On-site gym Subsidised café Complimentary soft drinks On-site bar Secure cycle storage and shower facilities Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Remote - Argentina; Brazil;Chile; Costa Rica Why You'll Love This Role: In this role, you will have the opportunity to directly shape our data ecosystem by building robust pipelines and applying modern software engineering principles like version control and automated testing. You’ll work closely with key stakeholders to drive data-driven decision-making, lead high-impact initiatives, and manage large-scale infrastructure and automation. You will lead and mentor junior engineers and set the technical direction for the analytical team. If you thrive on transforming complex data into reliable, actionable insights while building scalable analytics systems, this position offers the ideal platform to showcase and expand your expertise. What You'll Be Doing: Set the technical direction for the analytics team (architecture, conventions, approach). Raise the technical floor through code review, design reviews, and pairing, holding a consistent bar for what ships. Own the architecture of our data models, with accountability for long-term maintainability rather than just the models you write yourself. Own the semantic layer, metric definitions, and governed self-service, so stakeholders can answer their own questions correctly. Act as the primary technical partner to Product, Finance, Marketing, and Engineering, translating what they need into a roadmap the team can execute. Negotiate scope directly with stakeholders. Drive a cadence of proactive analysis so the team surfaces questions the business hasn't asked, rather than waiting for tickets. Define the team's data testing strategy and govern how business logic is validated across the analytics layer. Own the operational health of the analytics layer (monitoring, alerting, incident response, and release readiness for what the team ships). Mentor the engineers around you and build shared understanding through documentation and technical presentations. Lead large-scale migrations and performance efforts, setting the approach and enabling the team to execute rather than executing alone. About You: 8+ Years experience working with data in a software environment. Required Skills: Mastered proficiency in SQL and Python; advanced experience managing business semantic layer tooling, data catalog tooling and  data integrity testing frameworks. Experience with dbt orchestration and best practices. You have a track record of working autonomously and proactively, with deep domain knowledge of data analysis and data systems. Required Tech Stack: SQL, Python, relational datastores, DAG tooling (like Dagster or Airflow), dbt and Tableau. Experience with cloud-based infrastructure (AWS, GCP, Terraform) and document, graph, or schema-less datastores. Why you’ll love working at Newsela: Make A Difference: No matter your role or department, the work you do each day helps share the future of education and improves the lives of students and teachers. All offers of employment are contingent upon the successful completion of a background check as part of our pre-employment process. About Newsela: Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner. #LI-Remote

Location: Worldwide Workplace: remote We are looking for a Data Governance Analyst to join our team.RequirementsBusiness Metrics & Data Governance: experience documenting and standardizing business metrics, KPIs, business glossary, and business logic to establish a single source of truth across the organization.Data Quality: hands-on experience translating business requirements into measurable Data Quality rules and implementing automated validation using Great Expectations, Soda, dbt Tests, or similar frameworks.SQL & Python: strong SQL and Python skills for data validation, automation, framework development, and root cause analysis of data quality issues.Metadata Management: experience with data catalog and metadata management platforms (OpenMetadata, DataHub, or similar) to maintain metadata, lineage, and documentation.Data Governance Principles: solid understanding of Data Governance, Data Stewardship, Data Lineage, Metadata Management, and Data Lifecycle Management to support scalable governance practices.AI: practical experience using AI tools to automate workflows, improve productivity, and enhance data analysis and documentation processes.Nice to haveExperience with streaming technologies (Kafka, Spark, Flink).Experience with orchestration tools (Airflow, Dagster) and CI/CD.Experience with semantic/metrics layer tools (dbt Semantic Layer, Cube, LookML).Knowledge of data privacy and security standards (GDPR, CCPA).Previous experience in iGaming or FinTech.ResponsibilitiesDefine and standardize business metrics, KPIs, and business glossary together with stakeholders to ensure consistent business definitions across the company.Drive Data Governance adoption by introducing standards, best practices, and governance processes across data domains.Design and develop the company's Data Quality framework, including validation rules, monitoring, and quality standards to improve data reliability.Implement and maintain automated Data Quality checks and anomaly detection to proactively identify and resolve data issues.Build and manage the data catalog, metadata, and data lineage to improve data discoverability and transparency.Collaborate with Data Engineers to integrate Data Quality controls into data pipelines and investigate data inconsistencies across systems.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.