onsite
Data Platform Engineer - Liebherr-International Deutschland GmbH
Data Engineer
Lead the design, build, and maintenance of scalable data pipelines and lakehouse solutions using Python, SQL, and AWS services, ensuring high data quality and performance for enterprise analytics.
About the role
Key Responsibilities
- Architect and develop robust data pipelines and lakehouse solutions on AWS, leveraging services such as S3, Glue, Redshift, and Athena.
- Implement and maintain ETL workflows using Python, SQL, and Spark, ensuring data integrity and optimal performance.
- Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable data models and dashboards.
- Monitor, troubleshoot, and optimize pipeline performance, applying best practices for data quality, security, and governance.
- Document architecture, processes, and standards to support knowledge sharing and compliance.
Requirements
- Proven experience in data engineering with Python, SQL, and Spark.
- Hands‑on expertise with AWS data services (S3, Glue, Redshift, Athena).
- Strong understanding of ETL concepts, data modeling, and lakehouse architecture.
- Experience with workflow orchestration tools such as Airflow.
- Excellent problem‑solving skills and a collaborative mindset.
Skills
pythonsqlawsapache sparkairflow