Senior Data Engineer

1/2024 – offen

• Provided strategic guidance in managing and optimizing cloud data architecture, overseeing large-scale data
environments with multiple catalogs, and ensuring seamless governance and access control across diverse teams.
• Designed and implemented scalable Terraform modules for infrastructure automation, modularizing resource
management through flat file definitions, significantly reducing manual setup and increasing operational consistency.
• Developed comprehensive disaster recovery strategies for critical data systems, ensuring the backup and restoration of metadata and associated resources to separate regions for improved business continuity and resilience.
• Streamlined user management and access control processes by automating Databricks SCIM synchronization
with Entra ID, enhancing efficiency and simplifying the management of cross-platform data access.
• Delivered customized data reporting solutions to improve metadata discoverability, enabling data subscribers to
easily compare and navigate across legacy and modern data systems.
• Consulted on cloud data architecture and data pipeline solutions, delivering efficient ETL processes and eventdriven data workflows, optimizing data accessibility using Python, PySpark, and Databricks.
• Provided expertise in platform engineering, advising on event-based data processing, and creating Terraform
modules for infrastructure automation and RBAC access control to align with business needs.
• Led process automation initiatives across multiple teams, driving improvements in operational efficiency by
automating resource provisioning, data processing, and access management workflows

Databricks, Python, Microsoft Azure

10/2022 – 1/2024

• Led a team of 8 Data Engineers, managing roadmaps, mentoring, and conducting technical interviews.
• Designed scalable cloud data architecture with Enterprise and Domain Architects to align infrastructure with
business goals.
• Developed and optimized ETL pipelines using a custom Rule Engine Framework (Python, PySpark) to improve
workflow efficiency.
• Built an Event Creation Engine for efficient data processing using Rule Engine and Service Bus messaging.
• Created POCs for Terraform automation and Unity Catalog integration to enhance data governance.
• Developed Python modules to streamline ETL processes and ensure data quality.
• Managed CI/CD pipelines with Azure DevOps, speeding up deployments by 40%.
• Supported cross-functional teams with inner sourcing to improve collaboration and operational efficiency.

Apache Spark, Databricks, DevOps, Git, Java (allg.), Microsoft Azure, Python, Spring Framework

3/2021 – 10/2022

• Led a project development team of 10 Data Engineers, owning key data products and facilitating client meetings
to present tailored solutions.
• Designed and implemented ETL pipelines for cloud analytics platforms, transforming raw data with Spark and
loading data into the data warehouse, boosting data processing speed by 30%.
• Built and optimized cloud data architecture, including Data Lake (ADLS), Delta Lake, and Azure SQL Database,
improving system performance and data accessibility.
• Processed large datasets using Python, Spark, Scala, and MS SQL on Databricks, which led to a 25% reduction
in data processing time and greater overall reliability.
• Developed custom Python packages for efficient data processing and created PowerBI dashboards, which helped
reduce manual reporting time by 50%.
• Managed CI/CD pipelines with Azure DevOps, achieving 100% code test coverage through unit and integration
testing, while implementing monitoring solutions that decreased data ingestion errors by 60%.
• Onboarded and mentored new team members, fostering team growth and enhancing overall collaboration within
the group.
• Collaborated with cross-functional teams to provide technical guidance and ensured smooth integration across
project streams, resulting in more efficient project delivery.

DevOps, Apache Spark, Databricks, Git, Microsoft Azure, Power Bi, Python, Scala