artur lauth

I’m a Data Engineer with 3.5+ years of experience solving problems using technology and methodology. I approach modern data architectures by treating data as a software product—bringing software engineering best practices, data quality validations, and automated testing across bronze and silver layers to ensure long-term scalability and sustainability.

In my current role at Compra Agora (Unilever), I act as technical support for BI, Analytics, and Data Engineering teams, helping translate business needs into data models and manage architecture requirements cost-effectively. I’ve maintained and evolved a Delta Lake data model to ensure correct granularity, metric consistency, and long-term analytical scalability while collaborating with Product, BI, and Operations to troubleshoot production issues and maintain data consistency and trust.

I drive measurable impact through optimization and problem resolution. I redesigned a high-throughput streaming pipeline—cutting a pipeline cost from 8.000 USD/month to 360 USD/month—using proper partitioning, Spark Structured Streaming micro-batching with Solace integration, and right-sized Databricks clusters based on workload throughput and latency.

I also focus on reliability, governance, and business value: I fixed a long-standing revenue issue caused by schema drift in vendor-sent XML invoice files, preventing an estimated 500K BRL in monthly revenue loss. To improve decision-making, I built a platform-level observability and DataOps layer by ingesting Databricks Jobs API metadata into analytical datasets and powering Databricks dashboards for monitoring and trend analysis.