Projects

Context

Department-wide reports depended on consistent data delivery and traceable transformations.

Challenge

High reliability expectations with enterprise infrastructure constraints and a strict production change process.

Technical approach

Designed metadata-driven ETL processes with clear data models, logging tables, and operational runbooks. Coordinated requirements with report designers and validated behavior under production-like volumes.

Outcome

Improved stability and operability, making failures easier to trace and reducing support effort during reporting cycles.

Context

New data models required large initial loads and daily deltas to support SAP Analytics Cloud consumers.

Challenge

Initial loads in the billions and daily deltas in the millions demanded careful chunking and runtime control.

Technical approach

Built batch-oriented processes orchestrated with Atomic and executed via a custom loader, using chunk strategies and monitoring tables for step-wise verification.

Outcome

Reliable runtimes under production pressure and predictable daily delivery for analytics consumers.

Context

Teams needed structured access to documentation for downstream embedding workflows.

Challenge

Unstructured documents and changing metadata required resilient ingestion and enrichment.

Technical approach

Extracted documents via REST APIs, enriched metadata, and stored structured outputs in S3 for downstream consumers.

Outcome

Created a stable document dataset that supports consistent downstream processing.