Data Engineering Technical Lead

Summary

Lead hands-on modernization of legacy SSIS/SSRS ETL workloads into cloud-native Lakehouse pipelines using Databricks, dbt, Fivetran, and Airflow. Design and enforce standardized data frameworks (ingestion, transformation, curation, consumption), drive CI/CD and observability practices, and mentor engineers on modern data engineering patterns. Evaluate emerging technologies (Delta Live Tables, Iceberg, streaming, AI-driven observability) through POCs and POVs, and leverage AI-assisted tools (Databricks Assistant, GitHub Copilot, Cursor AI) to accelerate development and reduce technical debt. Optimize Spark workloads and orchestration across Azure and GCP environments while partnering with architects, platform engineers, and business stakeholders.