Lead Data Engineer

📋 Description

• Lead the end-to-end migration of legacy Python/Spark ETL configurations into modular, maintainable
• Provide hands-on technical leadership, mentorship, code review, and delivery guidance to data
• Partner with internal client engineers to define migration priorities, technical standards, and
• Reverse-engineer existing Python ETL logic and translate it into scalable dbt SQL models, staging
• Design foundational shared macros, dimension tables, and medium-to-high-complexity domain models
• Implement dbt sources, incremental model patterns, and schema.yml tests, including not_null

🎯 Requirements

• 5+ years of production experience with dbt Core; dbt Certified Developer certification preferred
• Hands-on experience leading data engineering teams, mentoring engineers, reviewing code, and owning
• Advanced knowledge of dbt, including Jinja macros, sources.yml, schema.yml tests, reusable model
• Hands-on experience with Databricks, Delta Lake, Unity Catalog, and Databricks SQL Warehouses
• Advanced SQL skills, including CTEs, window functions, complex transformations, and Jinja templating
• Experience migrating custom or legacy Python-based ETL pipelines into modular, source-agnostic dbt