Python Data Engineer - W2 Role

Advanced SQL & Snowflake Optimization: Proven expertise writing production-level SQL (window functions, recursive CTEs, dynamic SQL, QUALIFY) and managing Snowflake environments (micro-partitioning, Time Travel, compute cost optimization, dynamic masking).Python Data Visualization: Mastery of Python libraries (Pandas, NumPy, Plotly, Seaborn, Dash/Streamlit) to build custom exploratory visualization apps and automated reporting suites.Enterprise BI & Dashboarding: Experience delivering high-impact executive dashboards (Power BI with DAX, Tableau with LODs, or Looker) focused on key financial metrics.Banking Domain Experience: Deep understanding of commercial or investment banking concepts, including portfolio risk monitoring, ledger reconciliation, and financial metrics (NIM, NPL, LTV, Risk-Weighted Assets).Governance & Security: Practical experience enforcing data governance policies (Row-Level Security, RBAC) to meet financial regulatory standards (SOX, PCI-DSS, GDPR).