Achieved SLA-driven, reliable data delivery to stakeholders
Reduced incident response time through proactive alerting
Optimized compute and data layouts for cost-efficient processing
Enabled reproducible environments with Terraform across dev and prod
Challenge
An energy company needed a robust cloud-based data platform supporting both batch and streaming workloads. Existing pipelines were unstable, lacked proper monitoring, and had no clear data governance.
Solution
I designed and operated a cloud-based Lakehouse-style data platform supporting batch and streaming ingestion, transformation, and analytical serving. Implemented Medallion architecture, distributed processing pipelines, and comprehensive CI/CD workflows.
My Role
Senior Data Platform Engineer – owned platform architecture, pipeline development, infrastructure-as-code, and monitoring setup.
Key Deliverables
- 01Lakehouse platform with Delta Lake and Medallion architecture
- 02PySpark and Golang-based data pipelines with deterministic processing
- 03GitHub Actions CI/CD for automated testing and deployment
- 04Monitoring and alerting with structured logging and failure notifications
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