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Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Design, develop, and maintain production data pipelines using Python, Apache Airflow, Snowflake, and Amazon S3 Design and evolve scalable data architectures, including Bronze, Silver, and Gold data layers Develop data models and implement incremental loading, historization, versioning, and reusable transformation patterns Write and optimize complex SQL transformations, views, stored procedures, dynamic tables, streams, tasks, and scheduled jobs Integrate data from relational databases, APIs, object storage, and file-based sources Implement data-quality checks, validation, reconciliation, lineage, monitoring, and robust error-handling processes Manage Snowflake access controls, roles, permissions, service accounts, and deployment across development, staging, and production environments Maintain CI/CD pipelines for Snowflake objects, Airflow DAGs, and Python code using Git and automated testing Monitor and troubleshoot production pipelines and proactively improve reliability and performance Collaborate with data, analytics, engineering, and other technical teams to translate business and technical requirements into reliable data products Create technical documentation and specifications following established quality and compliance standards What we expect : 5+ years of experience in Data Engineering, including at least 3 years working with production data platforms Strong hands-on experience with Snowflake, including Data modeling, RBAC and access management, Warehouse management, Query profiling and performance optimization, Stored procedures Advanced SQL skills, including complex joins, CTEs, window functions, incremental processing, and query optimization Strong Python skills for ETL, database integration, automation, error handling, and testing Production experience with Apache Airflow, including DAG development, dependencies, sensors, task groups, retries, backfills, and operational support Experience working with relational databases, object storage, APIs, and file-based data sources Strong understanding of modern data architectures, including medallion and dimensional modeling, slowly changing dimensions, natural and surrogate keys, and historization Experience with Git, pull requests, automated testing, and CI/CD for data pipelines and database code Strong problem-solving skills and the ability to work independently in a production environment Snowflake and Apache Airflow are core requirements for this role; experience only with alternative data warehouses or orchestration tools would not be sufficient Nice to have : Experience working in regulated or validated environments Background in life sciences, healthcare, clinical, laboratory, genomic, or bioinformatics data Experience working with LIMS or other scientific/clinical data systems Familiarity with OMOP or other standardized clinical data models Experience with data-consumption and visualization tools such as Tableau or Streamlit Familiarity with scientific or computational workflows and tools such as Nextflow or similar workflow orchestration platforms SnowPro certification Experience with AWS Managed Workflows for Apache Airflow (MWAA) We offer : Competitive compensation Remote work Flexible working hours A team with excellent tech expertise

О ПРОЕКТЕ VADAROD расширяет команду! Мы ищем эксперта, который усилит нашу работу с данными и поможет вывести КХД на новый уровень. Если ты мастерски владеешь DBT и знаешь, как строить отказоустойчивые модели данных — нам по пути! ТВОИ КЛЮЧЕВЫЕ ВЫЗОВЫ — Transformation: Создание эффективного слоя трансформации сырых данных. — Modeling: Проектирование концептуальных, логических и физических моделей данных для КХД. — Architecture: Прямое участие в разработке архитектуры решений. — Quality: Участие в Code Review и внедрение лучших практик разработки. МЫ ЖДЕМ ОТ ТЕБЯ — Tooling: Уверенный опыт работы с DBT, CDC или Databricks. — Coding: Знание Python и умение писать/отлаживать действительно сложные SQL-запросы. — Design: Практические навыки проектирования баз данных и хранилищ (DWH). БУДЕТ ПЛЮСОМ — Опыт в финтех-домене или понимание процессов финансовых организаций. — Работа с Apache Airflow, Debezium или Greenplum.

Location: The Netherlands; United Kingdom; Spain; Germany Workplace: Remote ABOUT THE ROLE At ClickHouse, we believe in making product decisions grounded in data, not gut feelings. To support that, we've built a comprehensive internal data warehouse — read more about it on our blog https://clickhouse.com/blog/building-a-data-warehouse-with-clickhouse. It powers analytics, forecasting, and decision-making across every team in the company. Our stack centers on ClickHouse as the core storage and processing engine, complemented by dbt, Airflow, S3, AWS, Superset, and GitHub Actions. We ingest data from 30+ distinct external sources, process over 2.5 PB of data, and deliver most data marts to business consumers with a 1-hour end-to-end latency - a standard that demands highly optimized, rock-solid transformation pipelines. We're looking for a Senior Data Engineer to help evolve the DWH platform, push its technical boundaries, and deliver reliable, high-performance data models to business users across the organization. KEY RESPONSIBILITIES 1. DWH Platform Development - Design and develop reusable Airflow components - operators, connectors, and hooks - along with custom integrations tailored to our data architecture. - Build reusable dbt macros and abstractions: incremental strategies, ETL building blocks, and generic data quality tests, all optimized for ClickHouse-specific behavior and our data patterns. - Develop DataOps tooling - CI pipelines, data migration frameworks, and security controls - with a strong focus on reliability, self-service usability, and scale. 2. Team contributions - Conduct thorough code reviews for team members and other team contributors. - Actively participate in technical and architectural design discussions. - Drive technical leadership in specific areas of our stack. - Continuously improve the team's development environment, with a focus on automation - including AI-assisted workflows. - Contribute to platform stability through proactive troubleshooting and timely incident resolution. 3. Data modeling - Develop, refactor, and optimize business data models in line with our modeling standards and ClickHouse best practices. - Mentor and support contributors through code reviews and technical guidance. - Lead the design and implementation of the most technically demanding data marts - particularly those involving high data velocity, large volumes, or complex business logic. QUALIFICATIONS Required: - Exceptional SQL skills - this is non-negotiable. - Strong hands-on experience with Airflow, dbt, and Python. - Proven track record building and optimizing large-scale, high-throughput data pipelines. - Solid understanding of data warehousing fundamentals: ETL/ELT, dimensional modeling, and data quality. - Bachelor's degree in Computer Science or a related field. - Comfortable thriving in a fast-paced startup environment — exciting and dynamic, but sometimes wonderfully chaotic. Preferred: - Hands-on experience with ClickHouse - a significant advantage. - Familiarity with AWS or other cloud platforms. - Experience with CI/CD development, especially using GitHub Actions. 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: Portugal Workplace: remote *ALL CANDIDATES MUST BE LOCATED IN PORTUGAL* About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote, this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. Are you ready to make your mark? About the Role We are looking for a Site Reliability Engineer (SRE) to improve the reliability of our AI and analytics platforms and the services that depend on them. As Intermedia expands its global product deployments, this role will strengthen SRE practices across production infrastructure, data pipelines, machine-learning services, customer-facing analytics, and AI-powered Voice and Unified Communications capabilities. You will partner with AI, data, product, and platform teams to build scalable, observable systems that deliver dependable insights and resilient customer experiences. What you will be doing: Run and improve production environments that support AI and AI workloads, data pipelines, analytics applications, and customer-facing services. Build software and automation to manage cloud infrastructure, data platforms, model-serving infrastructure, and application services. Define and measure service level indicators, service level objectives, and error budgets for AI and analytics services, including availability, data freshness, pipeline completion, and inference latency. Build end-to-end observability that correlates metrics, logs, and traces with data-quality signals, AI-service performance, and customer impact. Monitor and optimize the reliability, performance, capacity, and cost of batch and streaming workloads, analytics queries, and inference services. Partner with data engineering and machine-learning teams to make ingestion, transformation, feature, training, deployment, and reporting workflows production-ready. Automate CI/CD and production-readiness checks for data pipelines, model and prompt releases, schema changes, analytics applications, and dashboards. Detect and resolve data-quality incidents involving missing, stale, delayed, or anomalous data, schema drift, and broken lineage or dependencies. Design and test graceful degradation, dependency isolation, retry and fallback patterns, and recovery procedures for impaired AI, data, or downstream services. Improve the reliability of AI-powered Voice and Unified Communications capabilities such as speech recognition, transcription, summarization, intelligent routing, conversational assistance, and text-to-speech. Establish operational monitoring for model and AI-service behavior, including latency, throughput, error rates, drift indicators, and changes in output quality. Plan capacity and run performance, load, and resilience tests across compute-intensive AI workloads, distributed data processing, and analytics services. Lead incident response and post-incident improvement for AI and analytics services, using measurable actions to reduce recurrence and recovery time. Support secure and reliable access to cloud storage, processing, and query services used by analytics products and internal decision-making. Reduce operational toil and improve engineering productivity through platform tooling, runbooks, self-service automation, and clear operational standards. What you will bring to the role: Bachelor's degree in computer science, data engineering, software engineering, or another technical or scientific discipline, or equivalent practical experience. 4-7 years of experience in production operations, systems engineering, SRE or DevOps, software deployment, and maintenance of distributed production systems. Experience with cloud infrastructure, containers, Kubernetes, distributed systems, and scalable compute and storage services. Experience operating data processing, orchestration, storage, or analytics technologies, such as Kafka, Spark, Airflow, dbt, data warehouses, or comparable cloud services. Ability to use metrics, logs, traces, data-quality checks, freshness indicators, lineage, and service-level indicators to diagnose complex production issues. Experience with CI/CD, DataOps or MLOps practices, automated testing, controlled rollout, and rollback of data and AI service changes. Strong troubleshooting skills across Linux, applications, networks, APIs, data pipelines, and distributed service dependencies, with attention to security and access controls. Strong analytical problem-solving and cross-functional communication skills, with a proactive approach to reliability, performance, and continuous improvement. Diversity Inclusion and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: Portugal Workplace: remote *ALL CANDIDATES MUST BE LOCATED IN PORTUGAL* About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote, this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. Are you ready to make your mark? About the Role We are looking for a Site Reliability Engineer (SRE) to improve the reliability of our AI and analytics platforms and the services that depend on them. As Intermedia expands its global product deployments, this role will strengthen SRE practices across production infrastructure, data pipelines, machine-learning services, customer-facing analytics, and AI-powered Voice and Unified Communications capabilities. You will partner with AI, data, product, and platform teams to build scalable, observable systems that deliver dependable insights and resilient customer experiences. What you will be doing: Run and improve production environments that support AI and AI workloads, data pipelines, analytics applications, and customer-facing services. Build software and automation to manage cloud infrastructure, data platforms, model-serving infrastructure, and application services. Define and measure service level indicators, service level objectives, and error budgets for AI and analytics services, including availability, data freshness, pipeline completion, and inference latency. Build end-to-end observability that correlates metrics, logs, and traces with data-quality signals, AI-service performance, and customer impact. Monitor and optimize the reliability, performance, capacity, and cost of batch and streaming workloads, analytics queries, and inference services. Partner with data engineering and machine-learning teams to make ingestion, transformation, feature, training, deployment, and reporting workflows production-ready. Automate CI/CD and production-readiness checks for data pipelines, model and prompt releases, schema changes, analytics applications, and dashboards. Detect and resolve data-quality incidents involving missing, stale, delayed, or anomalous data, schema drift, and broken lineage or dependencies. Design and test graceful degradation, dependency isolation, retry and fallback patterns, and recovery procedures for impaired AI, data, or downstream services. Improve the reliability of AI-powered Voice and Unified Communications capabilities such as speech recognition, transcription, summarization, intelligent routing, conversational assistance, and text-to-speech. Establish operational monitoring for model and AI-service behavior, including latency, throughput, error rates, drift indicators, and changes in output quality. Plan capacity and run performance, load, and resilience tests across compute-intensive AI workloads, distributed data processing, and analytics services. Lead incident response and post-incident improvement for AI and analytics services, using measurable actions to reduce recurrence and recovery time. Support secure and reliable access to cloud storage, processing, and query services used by analytics products and internal decision-making. Reduce operational toil and improve engineering productivity through platform tooling, runbooks, self-service automation, and clear operational standards. What you will bring to the role: Bachelor's degree in computer science, data engineering, software engineering, or another technical or scientific discipline, or equivalent practical experience. 4-7 years of experience in production operations, systems engineering, SRE or DevOps, software deployment, and maintenance of distributed production systems. Experience with cloud infrastructure, containers, Kubernetes, distributed systems, and scalable compute and storage services. Experience operating data processing, orchestration, storage, or analytics technologies, such as Kafka, Spark, Airflow, dbt, data warehouses, or comparable cloud services. Ability to use metrics, logs, traces, data-quality checks, freshness indicators, lineage, and service-level indicators to diagnose complex production issues. Experience with CI/CD, DataOps or MLOps practices, automated testing, controlled rollout, and rollback of data and AI service changes. Strong troubleshooting skills across Linux, applications, networks, APIs, data pipelines, and distributed service dependencies, with attention to security and access controls. Strong analytical problem-solving and cross-functional communication skills, with a proactive approach to reliability, performance, and continuous improvement. Diversity Inclusion and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Задачи: сбор и уточнение требований от маркетинговых аналитиков и BI, их перевод в изменения логики атрибуции, источников и data marts; миграция attribution-пайплайна (dbt-модели, Airflow DAGs, источники) на core DWH-платформу с параллельным прогоном старого и нового контуров и сверкой до переключения;

Задачи: — Разработка и поддержка автотестов на Python с запуском в CI/CD. — Тестирование REST и SOAP API, интеграций с Kafka и Elasticsearch. — Проверка пайплайнов обработки данных и валидация результатов в базе данных с использованием SQL. — Составление тест-планов и чек-листов, оформление дефектов и приоритезация тестовых сценариев по важности для бизнеса. Требования: — Опыт разработки автотестов на Python от 5 лет с использованием pytest или unittest. — Опыт работы с CI/CD системами Jenkins и GitLab CI. — Уверенное владение SQL, включая написание запросов с JOIN и оконными функциями. — Опыт тестирования REST и SOAP API, интеграций с Kafka и Elasticsearch. — Опыт тестирования пайплайнов Spark, Airflow, NiFi и Dolphin. — Навыки подготовки тест-планов, чек-листов и отчетов о дефектах. — Умение приоритезировать тестовые сценарии с учетом бизнес-критичности. Будет плюсом: — Опыт написания unit-тестов на JUnit или TestNG.

Location: Hamburg Workplace: Hybrid adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually. Architecting Intelligence to Optimize 200M+ Daily Decisions As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time. Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange. Engineered for performance, our stack leverages PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem. The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second. Your Mission & Who We Are Looking For - Quantitative Academic Foundation: You are currently pursuing a Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field. You are available to contribute up to 20 hours per week during the semester. - ML Model Prototyping: You will support the research and evaluation of deep learning and machine learning models that predict user behavior across our 770 million user base. We are looking for solid Python skills and hands-on familiarity with PyTorch, TensorFlow, scikit-learn, and gradient boosting libraries (LightGBM/CatBoost/XGBoost) to prototype new algorithms. - Large-Scale Data Exploration: Operating on our 1PB+ behavioral data lake, you will extract patterns from terabytes of data to engineer high-fidelity features for our training pipelines. This requires strong SQL fundamentals, an interest in distributed query engines (AWS Athena, Trino, Spark), and fluency with pandas, polars, and NumPy. - Experimentation & Validation: You will collaborate closely with our data scientists to test your fit-for-purpose solutions against our multi-objective optimization problem. We need someone who can rigorously evaluate models through offline experiments and A/B tests before they hit our 100,000+ predictions-per-second production environment. - Plus: ML Infrastructure Exposure: Any prior exposure to the systems that run our real-time scale—AWS, workflow orchestration (Airflow), containerization (Docker), or basic model deployment workflows—will accelerate your impact. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. Skip writing cover letters. Tell us about your most passionate personal project, your desired salary, and your earliest possible start date. We are looking forward to your application! We welcome applications from people who will contribute to the diversity of our Company. We welcome applications from people who will contribute to the diversity of our company.

Требования: — Опыт работы с Python не менее 5 лет, умение писать production-ready код и использовать паттерны проектирования. — Знание и опыт работы с Docker и Kubernetes. — Опыт работы с Apache Airflow. — Навыки работы с Apache Kafka и REST API. — Знание баз данных и распределённых вычислений. — Опыт использования GitLab CI или GitHub Actions. — Навыки мониторинга с Prometheus и Grafana. — Владение системой контроля версий Git. — Будет преимуществом понимание жизненного цикла MLOps. — Опыт работы с Feature Store и DVC. — Базовые знания машинного обучения, глубокого обучения и методов валидации моделей. — Опыт работы с Apache Spark и Hadoop. Локация: удалённо, Москва или Санкт-Петербург. Требуется гражданство РФ. Оформление через ИП или самозанятость.

Задачи: — Развитие продукта, построение системы работы с данными, усиление процессов и консультирование бизнеса по вопросам точек роста. — Анализ игровой экономики, баланса, поведения игроков и других аспектов игрового продукта. Требования: — Опыт работы продуктовым или маркетинговым аналитиком не менее 2,5 лет, общий опыт в аналитике от 4 лет. — Высшее физико-математическое или техническое образование и/или быстрый карьерный рост в крупных продуктовых компаниях с большим объемом данных (например, Avito, Yandex, inDrive). — Уверенные технические навыки в SQL, Python, мощная математическая и статистическая база, опыт работы с AB-тестами. Условия: — Работа удалённо из любой страны, при этом у компании есть офисы в Армении, Грузии, Казахстане, Сербии, Кипре. — Использование современного технического стека: databricks, pyspark, AWS, Appsflyer, Amplitude, S3, Airflow, Redshift, Monte Carlo. — Аналитики работают с данными через SQL и Python в Jupyter/Databricks ноутбуках, создают прототипы дашбордов в Tableau.

Требования: — Необходим опыт работы с Python, SQL, PyTorch, Scikit-learn и Pandas. — Практические навыки использования FastAPI и Pydantic. — Опыт полного цикла разработки ML-моделей: от постановки задачи и подготовки данных до внедрения в production и поддержки. — Знание техник оценки ML-моделей, включая time-aware validation, backtesting, holdout datasets, calibration и error analysis. — Опыт создания CI-based regression suites для контроля качества моделей. — Навыки работы с model serving, MLOps, experiment tracking, model registries и контейнеризацией. — Опыт мониторинга моделей, выявления data drift и model degradation, а также организации переобучения. — Понимание вопросов data privacy, PII и тестирования на утечку приватных данных. — Опыт uncertainty quantification и работы с prediction intervals. — Дополнительным плюсом будут знания embeddings, retrieval systems, synthetic data generation, differential privacy, geospatial data, LangGraph, Airflow, Step Functions, а также опыт в сфере недвижимости и финансов. Задачи: — Разработка и внедрение ML-моделей для прогнозирования occupancy, headcount, rent и финансовых показателей. — Оценка качества моделей, проведение backtesting и анализ ошибок. — Разработка и поддержка ML-сервисов, API и MLOps-процессов. — Мониторинг production-моделей, контроль drift и degradation, организация переобучения. — Работа с embedding и retrieval-системами, synthetic data pipelines. — Взаимодействие с командами Product, Platform Engineering и Data Platform. Условия: — Только для фрилансеров, аустафф и рекрутинговые компании не рассматриваются. Требуемый уровень английского языка: B2. Опыт работы: от 5 лет на позиции Senior с навыками Python и SQL. География: LATAM.

Задачи: — Развивать корпоративное хранилище данных, проектировать витрины под управленческую и финансовую отчетность. — Разрабатывать процессы сборки витрин и подключать новые источники данных. — Взаимодействовать с сотрудниками банка для выявления и уточнения требований, разбираться в методологии расчетов и согласовывать результаты. — Предлагать варианты реализации с оценкой трудоемкости и ограничений. — Решать ad-hoc запросы бизнеса, быстро находить данные и объяснять расхождения в цифрах. — Разрабатывать отчеты и дашборды. — Готовить сопроводительную документацию, включая описание витрин и регламент расчета показателей. Требования: — Опыт работы аналитиком и/или инженером данных от 6 лет, из них от 2-3 лет в банковской сфере обязательно. — Экспертное знание SQL, включая оконные функции, аналитические запросы и сложные соединения. — Навыки оптимизации запросов, включая чтение плана выполнения, работу с большими таблицами, партиционирование и индексы. — Опыт работы с промышленными СУБД. — Опыт развития хранилища данных, включая проектирование витрин и разработку ETL/ELT процессов. — Умение эффективно общаться с бизнесом, задавать уточняющие вопросы и понимать методологию. Будет плюсом: — Высшее техническое или экономическое образование. — Опыт работы с Airflow, Informatica, FormIT. — Опыт разработки дашбордов в BI-инструментах. — Знание финансов и бухгалтерского учета, опыт построения отчетности по этим направлениям. — Опыт работы с регуляторной отчетностью. Условия: — Оформление через ИП. — Удалённый формат работы. — Локация: Россия. — Уровень дохода обсуждается индивидуально.

Задачи: ▫️ Управление пайплайнами данных: batch и CDC-загрузки, трансформации, оркестрация, разбор инцидентов. ▫️ Разработка технических решений: физическая модель данных, структура dbt-проекта, шаблоны. ▫️ Руководство командой из 6–7 дата-инженеров и аналитиков: декомпозиция задач, код-ревью, найм и развитие сотрудников. ▫️ Поддержка AI-разработки: навыки, автопроверки, CI, контекст для AI-агентов. ▫️ Обеспечение качества данных: code review, контроль качества данных, сверка с источниками, мониторинг. ▫️ Обеспечение безопасности: управление доступами, секретами, аудит, взаимодействие с ИБ банка. ▫️ Управление контурами Dev / UAT / Prod: релизы, перенос данных с обезличиванием. ▫️ Выступать технической точкой контакта для банка и смежных команд. Требования: ▫️ Опыт работы в data engineering не менее 7 лет, из них минимум 2 года на позиции технического лидера. ▫️ Готовность активно писать код самостоятельно. ▫️ Опыт построения DWH или Lakehouse, понимание типичных проблем и их решений. ▫️ Экспертные знания SQL, уверенное владение Python, опыт моделирования данных (SCD, историчность). ▫️ Опыт работы с Iceberg, Trino, Spark, dbt, Airflow или аналогичными технологиями. ▫️ Умение аргументировать технические решения и объяснять компромиссы. ▫️ Опыт работы в банковской или другой строго регулируемой среде. Плюсом будет: ▫️ Опыт работы с CDC (Debezium, Kafka Connect), Ansible или другими инструментами Infrastructure as Code. ▫️ Опыт создания платформы данных с нуля. Условия: ▫️ Удалённая работа с необходимостью приезжать в Ереван 1–2 раза в месяц на 2–3 дня, при этом логистика и проживание оплачиваются. ▫️ Оформление через ИП. ▫️ Зарплата обсуждается индивидуально.

Location: Georgia On behalf of NDA, SaaS e-commerce , SD Solutions is looking for a talented Senior MLOps Engineer (Data & ML Platform) based in Georgia (Tbilisi) to join our growing team. You’ll own the data that Falcon’s offer-ranking model learns from: the raw sources, the pipelines, the training tables, and the monitoring around them. SD Solutions is a staffing company operating globally. Contact us to get more details about the benefits we offer. Responsibilities: What you’ll do: Own the ML data pipelines: build and run batch pipelines on Spark and Databricks, from raw data to feature and training tables, including enrichment and backfills for late-arriving data. Onboard new data sources: bring in internal databases, external APIs, partner feeds and web data, and match them to Falcon’s own entities. Use LLMs inside pipelines: add LLM steps to batch jobs, such as turning text into embeddings and structured attributes. Keep training and serving consistent: make sure features match between training and the live inference service, which includes reading its Java code. Monitor data and model inputs: run scheduled data quality checks and Grafana alerts that catch bad data before it reaches the model, and find the root cause when something breaks. Ship like an MLOps engineer: deploy pipelines through CI/CD (GitHub Actions, Docker, AWS) with proper secrets handling, and keep run time and cost under control. Work with AI agents: coding agents write most of Falcon’s code. You’ll decide where agents fit, then check their output on row counts, distributions and edge cases before anyone relies on it. Requirements: 5+ years in data engineering, MLOps or ML platform roles, with pipelines you’ve run in production Production Spark: complex transformations, window functions, large joins, partitioning, and tuning for shuffles and skew. Databricks (jobs, Delta tables) is a big plus. Production Snowflake: SQL, loading and unloading, and cost management Large data volumes: hundreds of millions of rows a month, with incremental loads and backfills that keep run time and cost under control Strong Python: clean, tested code; Spark UDFs including pandas UDFs; pandas and PyArrow Data quality and monitoring: quality checks, drift and anomaly detection, and alerts people can act on Deployment: GitHub Actions, Docker, AWS (S3, IAM) and proper secrets handling Backend engineering: comfortable working in a service codebase, not only in notebooks and SQL AI-first habits: you already use coding agents daily and look for what to automate Fluent English and based in Georgia Nice to have: MLflow and feature stores Airflow or Databricks Workflows Kafka or Spark Structured Streaming Terraform DBT Scala for Spark Reading Java Time-based splits and preventing data leakage in training sets Ad-tech or e-commerce data experience About the company: NDA helps eCommerce brands boost revenue with highly relevant and rewarding post-purchase offers. Our platform delivers personalized offers to customers right after checkout, driving repeat purchases and increasing lifetime value through seamless integrations and data-driven insights By applying for this position, you agree to the terms outlined in our Privacy Policy. Please take a moment to review our Privacy Policy https://sd-solutions.breezy.hr/privacy-notice , and make sure you understand its contents. If you have any questions or concerns regarding our Privacy Policy, please feel free to contact us.

Задачи: — организация пайплайнов потоков данных (конвейера движения данных в компании); — разработка, поддержка и оптимизация производительности Корпоративного Хранилища Данных (EDWH); — разработка и настройка ETL/ELT-процессов в Корпоративное Хранилище Данных (сбор, структурирование и обеспечение сохранности данных); — настройка инфраструктуры для обеспечения качества данных; — разработка BI дашбордов, визуализации данных. Требования: — опыт работы с технологиями Greenplum или другой MPP СУБД, ClickHouse, Airflow; — хорошее знание SQL и реляционных баз данных (желательно Greenplum или PostgreSQL), опыт написания сложных запросов; — хорошее знание Python; — знание современных технологий обработки больших данных; — высшее образование (IT/математика/математическая статистика/физика). Условия: — официальное трудоустройство (белая ЗП, отпуск, больничный); — льготы сотрудника аккредитованной ИТ компании (ипотека, отсрочка от армии); — ДМС со стоматологией, льготное ДМС для родственников; — компенсация оплаты больничного до оклада; — оплата мобильной связи, материальная помощь, скидки на занятия иностранными языками, оплата профессионального обучения, посещения конференций, компенсация процентов по ипотеке; — возможность профессионального и материального роста; — ежегодные выездные IT конференции, митапы, техтолки; — возможность стать амбассадором компании; — регулярные встречи вне офиса.

Location: Санкт-Петербург ИТ B2C - самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее. Мы, команда офиса CDO B2C, строим платформу данных, которая обеспечивает быстрый, надежный и качественный обмен информацией между Сбером и компаниями-партнерами. Это основа для персонализированных предложений умных продуктов и эффективных бизнес-решений. Наша команда - Команда развития Платформы в офисе CDO B2C ищет DE-инженера для реализации задач по загрузке, аналитике и трансформации данных. Обязанности проектировать и реализовывать ETL/ELT-пайплайны для загрузки и обработки данных (включая DAG в Apache Airflow) оптимизировать и сопровождать процессы обработки больших данных (Apache Spark, Apache Flink) интегрировать источники данных (базы данных, API, файловые хранилища) в единую pipeline-архитектуру настраивать и администрировать Airflow для оркестрации workflows участвовать в разработке архитектуры хранения и обработки данных (включая Hadoop-экосистему) документировать решения и формировать базы знаний. ### Требования наличие высшего образования опыт разработки ETL/ELT-процессов (реализация, оптимизация, мониторинг) профильное владение Python (включая библиотеки для работы с данными) практический опыт с распределенными вычислениями: Apache Spark (PySpark/Scala) или Apache Flink глубокое понимание SQL и опыт работы с РСУБД (PostgreSQL, MySQL и др.) знание Apache Airflow (создание DAG, настройка сенсоров, операторов) навыки администрирования Linux (развертывание, мониторинг, troubleshooting) **Будет преимуществом:** базовые знания Scala (или готовность к изучению) опыт с Hadoop (HDFS, YARN, Hive) знание облачных платформ (AWS S3/Glue, GCP BigQuery, Azure Data Factory) навыки автоматизации (Ansible, Terraform) опыт работы с стриминговыми данными (Kafka, Debezium). Условия гибридный формат ежегодный пересмотр зарплаты и годовая премия расширенный ДМС и льготное страхование для семьи уникальная система обучения Сбера для профессионального и карьерного развития выгодная ипотека для сотрудников подписка Прайм с возможностью совместного использования на трёх близких вознаграждение за рекомендацию друзей в команду Сбера корпоративная пенсионная программа.

Location: Espoo Workplace: Hybrid Software Engineer - SAR Processing Platform Role highlights: Job title: Software Engineer Location: Espoo, Finland Department: SAR Processing Platform Reports to: Team Lead SAR Processing Platform Employment type: Permanent Workplace model: Hybrid - 3 days in the office Employment is subject to applicable security screening (incl. SUPO, where required) Why this role matters: As a Software Engineer, you’ll help build and run the platform that every ICEYE image passes through before a customer sees it. The SAR Processing Platform validates raw radar data, decides when and where to process it, runs the processing workflows, catalogs the products and gates their delivery. You’ll join a small team that owns this orchestration layer end to end, covering how incoming data is validated, scheduled and processed, how products are cataloged and delivered, and the tools operators use to run it. The platform runs in the cloud and on on-premises clusters at customer sites, and you’ll work daily with SAR processing engineers, other engineering teams across the platform, DevOps, product and delivery. Who We Are ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world’s largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. Your day-to-day responsibilities - Build and maintain the backend services that schedule, process and catalog satellite data - Write and tune the processing workflows: resource sizing, reliability and integration of new processor versions - Keep production healthy: debug failed or stuck jobs from logs, metrics and the database, and turn recurring incidents into fixes or tooling - Ship through automated, version-controlled deployments to test, staging, production and on-prem environments, and roll out new processor versions and products with the SAR processing engineers using gradual rollouts and quality gates - Write tests, documentation and runbooks, and review teammates’ code What we’re looking for Must haves: - 2 to 5 years of backend software engineering experience, with solid Go and working Python, and willingness to read and occasionally change Rust - Hands-on Kubernetes and Docker as a developer: you have deployed, debugged and sized workloads yourself, not only used a cluster someone else ran - PostgreSQL (schema design, migrations, query debugging) and AWS fundamentals (S3, IAM, EKS or equivalent) - Experience running software in production, including incident debugging and postmortems - Pragmatic use of AI/LLM tools in daily development, fluent English, and comfort asking and answering questions in a distributed team Nice to haves: - Argo Workflows, Airflow or similar; NATS or Kafka; any Rust experience - Geospatial or remote-sensing data (GeoTIFF, COG, STAC, GDAL), or any large-file scientific data pipeline - Helm, Flux, Terraform; Prometheus, Grafana, OpenTelemetry Application Process 1. Recruiter Interview (30 mins online) 2. Hiring Manager Interview (60 mins online) 3. Technical Interview/ Task ( 60- 90 mins) 4. Onsite/ Final Interview (60 mins) Working at ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. How We Work (Our Values) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. Have fun: What we do matters, and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. Benefits Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. Our Commitment to Diversity, Equity, and Inclusion We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us, and we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Задачи: — Разработка Mobile Attribution SDK с нуля. — Создание real-time tracking и conversion APIs. — Разработка аналитических data pipelines. — Full-stack разработка продукта и интеграция со сторонними сервисами. Требования: — Сильный коммерческий опыт разработки на Python. — Уверенное владение SQL. — Практический опыт разработки JavaScript SDK и iOS SDK. — Опыт создания production-grade продуктов. — Понимание архитектуры ПО, API design и engineering abstractions. — Опыт обработки данных, интеграций и масштабируемых backend-систем. — Самостоятельность в принятии технических и архитектурных решений. — Английский — свободный. Будет плюсом: — React Native, Android SDK, Mobile Attribution / Analytics, GCP, Google Pub/Sub, BigQuery, Airflow, real-time streaming, event-driven architecture, tracking systems, advertising integrations, SaaS. Условия: — Работа до 22:00–23:00 по местному времени. — Локация: Европа. — Только фрилансеры, аустафф и рекрутинговые компании не рассматриваются.