Daniel Kovacs is a Senior Data Engineer and Solutions Architect with 12 years of experience designing scalable, cloud-native data platforms and ETL/ELT pipelines for finance, insurance, life sciences, and mobility clients. Based in Winterthur, Switzerland, he combines hands-on engineering (Databricks, Spark, Python, Azure/AWS) with architecture-level decision making, having led migrations, serverless designs, and performance optimizations that cut runtimes from hours to minutes. He mentors and builds cross-functional teams, authors clear architecture docs that accelerate governance approvals, and focuses on resilient, cost-effective solutions such as event-sourced ingestion and automated business record creation from emails. Practical innovations include migrating Pandas backends to Polars, introducing async Airflow execution, and designing a Python DSL for ingestion and lineage to scale developer productivity. He brings a curious, multidisciplinary background (including studies in solar energy engineering) and a track record of rescuing high-risk projects by decoupling monoliths and improving observability and onboarding.
12 years of coding experience
9 years of employment as a software developer
BSc Software Engineering, BSc Software Engineering at Technical University of Budapest
Master's degree Solar energy engineering, Master's degree Solar energy engineering at H枚gskolan Dalarna / Dalarna University
Contributions:7 pushes, 1 branch in 5 years 11 months
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