Job
Description
LocationBangalore/Hyderabad/Pune
Experience level8+ Years About the Role
We are looking for a technical and hands-on Lead Data Engineer to help drive the modernization of our data transformation workflows. We currently rely on legacy SQL scripts orchestrated via Airflow, and we are transitioning to a modular, scalable, CI/CD-driven DBT-based data platform.
The ideal candidate has deep experience with DBT , modern data stack design , and has previously led similar migrations improving code quality, lineage visibility, performance, and engineering best practices.
Key Responsibilities
Lead the migration of legacy SQL-based ETL logic to DBT-based transformations Design and implement a scalable, modular DBT architecture (models, macros, packages)Audit and refactor legacy SQL for clarity, efficiency, and modularityImprove CI/CD pipelines for DBTautomated testing, deployment, and code quality enforcementCollaborate with data analysts, platform engineers, and business stakeholders to understand current gaps and define future data pipelinesOwn Airflow orchestration redesign where needed (e.g., DBT Cloud/API hooks or airflow-dbt integration)Define and enforce coding standards, review processes, and documentation practices Coach junior data engineers on DBT and SQL best practicesProvide lineage and impact analysis improvements using DBTs built-in tools and metadata
Must-Have Qualifications 8+ years of experience in data engineeringProven success in migrating legacy SQL to DBT , with visible resultsDeep understanding of DBT best practices , including model layering, Jinja templating, testing, and packagesProficient in SQL performance tuning , modular SQL design, and query optimizationExperience with Airflow (Composer, MWAA), including DAG refactoring and task orchestrationHands-on experience with modern data stacks (e.g., Snowflake, BigQuery etc.)Familiarity with data testing and CI/CD for analytics workflows Strong communication and leadership skills; comfortable working cross-functionally
Nice-to-Have Experience with DBT Cloud or DBT Core integrations with Airflow Familiarity with data governance and lineage tools (e.g., dbt docs, Alation)Exposure to Python (for custom Airflow operators/macros or utilities)Previous experience mentoring teams through modern data stack transitions