5–8 years hands-on experience as a Data Engineer on Google Cloud Platform with fluency in both German and English, guiding the migration team through a large-scale legacy-to-GCP data and application migration
Go-to expert on GCP data pipelines; helps the team design, build, and validate scalable data workflows using Big Query, Dataproc, and Cloud Composer.
Key Responsibilities
- Act as SME on GCP data engineering patterns — Dataproc (Spark/Hadoop) jobs, Cloud Composer (Airflow) DAGs, and BigQuery data models used in the target architecture
- Guide the migration team in re-platforming legacy ETL/data warehouse jobs onto GCP, including orchestration design, job scheduling, and dependency mapping in Composer
- Design and build Dataproc pipelines to process and transform migrated data, ensuring parity with legacy business logic
- Collaborate with data engineers and migration leads to troubleshoot discrepancies during testing and validation of migrated pipelines
- Optimize BigQuery performance (partitioning, clustering, query design) and Dataproc cluster/job configuration for cost and efficiency
Required Skills
- Fluency in both German and English
- Hands-on experience with core GCP data services — BigQuery, Dataproc, Cloud Composer (Airflow), Cloud Storage
- Strong Python and/or PySpark skills for building and maintaining data pipelines
- Solid understanding of Airflow DAG design, scheduling, and dependency management
- Experience with SQL and data modeling for analytical workloads
Preferred / Nice-to-Have
- Prior experience on a legacy-to-cloud data migration project
- Familiarity with legacy ETL tools (Ab Initio) or on-prem data warehouses for migration context
- Experience with CI/CD for data pipelines (Cloud Build, Terraform)
- Exposure to job scheduling tools such as UC4, and relational databases (Oracle, SQL Server)
Qualifications
- Bachelor’s degree in computer science, Information Technology, or a related field (or equivalent practical experience)
