Data Engineer

Job Title: Data Engineer Location: Stockholm, Sweden-Hybrid 2days/week Job type: Contract Please apply if you are authorized to work in Sweden Apache Spark, Airflow Key Responsibilities1 Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs. 2 Collaborate with cross-functional teams to understand and translate business requirements into data solutions. 3 Ensure data quality, integrity, and governance by implementing best practices in data management. 4.Develop processes and data flows using tools like PySpark and Airflow. 5 Support and enhance data platforms, databases, and data warehouses to enable advanced analytics. 6 Implement CI/CD pipelines using GitHub Actions and JFrog for automated deployment and version control. 7 Troubleshoot data pipelines and address any issues with real-time, batch data processing, and integrations. Experience & Skills Requirements:Must have: • 5+ years of experience in data engineering, especially in cloud data warehouse environments. • Proven expertise in AWS Redshift — internals, WLM, distribution/sort keys, query execution plan analysis, optimization techniques. • Hands-on experience with Pyspark and Apache Airflow. • Strong SQL skills and deep understanding of query performance tuning in Redshift. • Solid understanding of data modeling principles, including dimensional modeling (Kimball), normalized models, and hybrid strategies. • Experience with monitoring tools (CloudWatch, Redshift Console) • Familiarity with data versioning, CI/CD, and collaborative development practices in dbt. Expertise in Airflow, AWS Glue