Feb 2022 – Present · 4 yrs 3 mos · Germany

• Pioneered IMMO Capital’s data engineering function as the first senior data engineer, partnering with a single colleague to build the entire data ecosystem from the ground up.
• Designed and implemented an end-to-end data system within just two months, using Fivetran for select data integrations, custom Airflow (MWAA) DAGs, and a dbt repository to transform and model data for real-time business insights.
• Selected AWS Managed Workflows for Apache Airflow (MWAA), Snowflake, and Looker to establish a robust, scalable, and high-performing modern data stack.
• Architected and deployed an in-house visualization platform using Apache Superset on AWS ECS with auto-scaling and strict security protocols, reducing reliance on Looker and significantly cutting reporting costs.
• Partnered closely with the principal architect to build out a data mesh architecture, leveraging event-driven systems with AWS MSK, MSK Connect, and Spark Streaming for real-time data ingestion and processing.
• Engineered a comprehensive data platform featuring custom SDKs for message serialization and deserialization, enabling reliable and standardized data exchange across teams.
• Developed APIs to seamlessly deploy development team data schemas to AWS Glue Schema Registry, ensuring consistent schema management and improved data quality.
• Deployed Kafka UI and integrated with AWS Glue Schema Registry, simplifying schema discovery, updates, and version tracking.
• Streamlined MWAA DAG deployments by creating a centralized Airflow library, allowing teams to define their data workflows via dagfactory YAML and automate the publishing process.
• Coordinated multiple AWS services—MSK, MWAA, ECS (Kafka UI, Kafka Connect, MWAA Tasks, Superset), and Lambda-based APIs—under a unified data platform architecture for end-to-end data processing.
• Managed GitHub-centric workflows and data contracts for Kafka topic creation and access control, ensuring robust data governance and compliance.