Top Data Engineer Jobs in Krakow

Design, develop, and maintain scalable cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate and optimize SQL Server/SSIS-based data warehouses, ensure data quality and performance for large datasets, and collaborate with BI teams to support analytics and reporting.

Design, build, and maintain cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate data from multiple sources with SQL Server/SSIS, optimize performance and scalability of large datasets, ensure data quality, and support BI reporting (Power BI).

The AI/ML Data Engineer develops solutions for ETL processes, implements data quality metrics, and adapts technologies for big data processing while leveraging AI/ML data platforms.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

The Senior Software Engineer will lead engineering teams, mentor junior engineers, and ensure system reliability and performance while developing backend services.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The Data Engineer will manage deployments of core infrastructure components, contribute to CI/CD pipelines, and support data engineering standards focusing on reliability and scalability.

The AI Data Engineer will design and build AI data pipelines, ensuring reliability and quality for predictive intelligence in the Large Market Model.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

The Full Stack Data Engineer will design and build scalable data pipelines, optimize Snowflake architecture, develop dashboards and analytics solutions, and collaborate with cross-functional teams to ensure data reliability and meet business requirements.

The Data Engineer will develop, maintain, and optimize data pipelines using Apache Airflow, manage database performance, and support Elasticsearch integration. Responsibilities include building ETL scripts, handling Unix/Linux operations, and implementing CI/CD pipelines in GitLab.

Design, build, and maintain scalable Azure-based data pipelines and solutions using Fabric/Data Factory and Python. Create and manage Power BI datasets, optimize workflows, and collaborate with business and engineering teams to deliver analytics and insights.

As a Principal Big Data Engineer, you will design scalable solutions, develop data pipelines, create features, and collaborate with various teams to enhance Akamai's data platform.

Join Guesty as a Data Engineer to build and maintain scalable data systems, optimize ETL processes, and collaborate across teams for data-driven operations.

Lead foundational data-engineering work to validate and re-engineer pipelines for an anonymized, centralized credit data lake. Harmonize schemas across entities, build dbt models and tests, implement data-quality suites (Great Expectations), entity resolution, anonymization controls, optimize Spark/Glue jobs, orchestrate pipelines (Airflow/Step Functions), and produce documented, feature-ready datasets and runbooks for a regulated UK/Ireland lending environment.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

Build and maintain Python-based data pipelines to extract, clean, transform, and load CRM, Back Office, and Jira financial data. Run monthly invoicing processes, generate client reports and Tableau dashboards, troubleshoot API and data issues, and collaborate with Sales, Account Management, Billing, Legal, and Integration teams to ensure data accuracy and insights.

The role involves designing scalable data pipelines and architectures, integrating multiple data sources, and ensuring data quality and governance within the CMDB and Asset Intelligence platform.

As a Data Engineer, you will build and maintain ELT data pipelines, develop dbt models, and work with cross-functional teams to ensure data quality and reliability.

Design, build, and maintain scalable data pipelines on GCP; optimize data models; ensure data quality; support legacy data migration; collaborate with teams; implement monitoring; contribute to data governance best practices.

As a Data Engineer II, you will design scalable data pipelines in AWS, develop SQL transformations, and enhance MLOps workflows, focusing on analytics and machine learning initiatives.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

Design and build analytics-ready datasets, enable self-service semantic layers, translate business questions into metrics, ensure data accuracy and freshness, implement testing and CI/CD for reporting and dashboards across Danaher operating companies.

The Data Engineer will design, build, and maintain scalable data pipelines, develop ETL workflows using Python and SQL, and optimize data processes to ensure reliability and performance.

The Staff Data Engineer will manage product analytics architecture, drive data modeling standards, design data systems, and provide technical leadership across teams to improve data insights and product capabilities.