Data Analyst - Data Engineer - Analytics Engineer

Apply analytics to evaluate whether signals justify action, not just describe history, while building the serverless infrastructure that makes those evaluations reliable. Experienced in identifying false positives that misdirect budget, capacity, or prioritization, I design explicit decision logic, test signal stability before scale or execution, and operationalize analyses through Python pipelines on GCP with Terraform, data contracts, medallion architecture, and zero-trust deployment.

Use Python to structure exploratory analysis, validate assumptions, and build production data pipelines. Experienced with Polars for large-scale processing, registry-driven data quality rule engines, and infrastructure scripting. Prioritize interpretability and decision safety over unnecessary complexity when outputs drive real-world actions.

Use SQL to interrogate large datasets, isolate meaningful patterns, and test assumptions behind business decisions. Comfortable with BigQuery and MSSQL, translating ambiguous questions into structured queries that surface risks, gaps, and decision-relevant insights.

Leverage spreadsheets to build transparent, decision facing analyses that support planning, capacity management, and operational control. Experienced in consolidating multi source data, enforcing data quality, and reducing decision latency through clear, actionable views.

Build Power BI dashboards and operational monitors that reduce decision latency and support planning, prioritization, and capacity management. Design decision-facing visualizations with explicit logic, dynamic sensitivity calibration, and clear action signals for stakeholders.