26 Data Engineer jobs in Ukraine available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The role involves developing and maintaining ETL/ELT pipelines for analytical reporting and supporting attribution models. Additionally, the engineer will ensure data quality, perform query optimization in Redshift, and provide stakeholder support for BI platforms.
Develop, maintain, and monitor robust data pipelines to process AST outputs, knowledge graph structures, and vector embeddings. Collaborate with engineering teams to normalize data and ensure consistency across automated documentation generation workflows.
Build, optimize, and maintain ETL pipelines to extract data from ERP systems and APIs into BigQuery. Design data models and implement quality checks to ensure scalable, data-driven business solutions.
Design and develop scalable, cloud-native data architectures and automated ETL/ELT pipelines using BigQuery and GCP. Collaborate with Data Science and product teams to create business-critical data marts and reliable data services for advanced analytics.
The role involves managing data collection and ingestion pipelines to support model training operations at scale. You will collaborate with scientists and leadership to optimize infrastructure and define the dataset roadmap for next-generation AI products.
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Own and deliver the year-end financial audit data workstream, including transactional data ingestion and reconciliation. Collaborate with accounting stakeholders to resolve data discrepancies and build robust reporting pipelines in Snowflake and Looker.
Build and maintain scalable data pipelines and products within a Snowflake-based platform. Migrate existing Alteryx workflows into governed, production-ready data solutions while collaborating with BI and Data Governance teams.
You will be responsible for building and maintaining data platforms including data warehouses and lakehouses using Azure technologies. Additionally, you will collaborate with stakeholders to gather requirements, support data governance, and address data quality issues.
You will build and maintain data platforms including data warehouses and lakehouses using Azure technologies. Additionally, you will collaborate with stakeholders to design data flows, support data governance, and address data quality requirements.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists to optimize data quality, throughput, and costs while shaping the AI team's dataset roadmap.
The Data Engineer will own and deliver data engineering tasks, integrations, and marketing systems while troubleshooting pipeline and data quality issues. They will collaborate cross-functionally to transform data across various platforms and support payment orchestration flows.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists to optimize data quality, cost, and throughput while shaping the AI team's dataset roadmap.
Design, develop, and maintain data models and ETL/ELT pipelines to support KPI and operational reporting. Collaborate with business stakeholders and software teams to deliver scalable reporting solutions using GCP and Looker Studio.
Design and optimize high-throughput data pipelines that integrate static code analysis, graph databases, and vector indexes. Collaborate with AI/ML engineers to maintain knowledge graph schemas and ensure data integrity across automated documentation runs.
Design, build, and operate robust data pipelines and lakehouse platforms to ingest and transform large-scale datasets. Collaborate cross-functionally to maintain data services, optimize performance, and ensure data accessibility across the organization.
Design, develop, and deploy data solutions, including the creation of dashboards and reports to provide business insights. Manage data ingestion, ETL processes, and performance tuning of complex SQL and DAX queries.
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The role involves building and optimizing data pipeline architectures and tooling to support analytics and machine learning platforms. Additionally, the candidate will supervise junior engineers and collaborate with development teams to create cross-functional solutions.
Design, develop, and deploy Power BI solutions and data models to provide advanced analytics and business insights. Manage data ingestion, ETL processes, and performance tuning for complex SQL and DAX queries within a TAX platform.
Design and implement scalable cloud-based data platforms and pipelines to power analytics, AI, and GenAI systems. Collaborate with cross-functional teams to ensure data governance, observability, and the delivery of production-grade data products.
The role involves designing and building scalable data pipelines to process real-time bid stream, impression, and revenue data from various programmatic sources, while developing real-time and batch processing systems for auction analytics and bid landscape modeling. Responsibilities also include creating data models for yield optimization and maintaining data warehouses optimized for ad-tech query patterns.
The role involves designing and building scalable data pipelines to process real-time bid stream, impression, and revenue data from programmatic sources, while developing ETL/ELT workflows to transform raw data into analytics-ready datasets. Responsibilities also include building real-time and batch processing systems for auction analytics and developing data models for yield optimization.
You will design, build, and maintain the analytical data layer using dbt and SQL to ensure reliable decision-making. You will also collaborate with cross-functional teams to translate business requirements into clean, reusable data models and maintain high data quality standards.
The Data Scientist will explore data to identify trends and evaluate campaign performance while designing and optimizing algorithms for CPA optimization. They will also collaborate with product teams to translate technical solutions into measurable business impacts.
Lead the data architecture for a new FX Trading Analytics platform, selecting and optimizing the big-data engine for real-time and historical analysis. Own the end-to-end installation, configuration, and scaling of the database environment to support massive datasets.
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