Lead Data Engineer(35)

- Core skills : DBT + Python + Pyspark + SQL + Data Modelling Concepts + any Cloud + Good communication Nice to have: GCP Minimum 8 yrs of industry experience We are looking for a lead profile with strong Data Engineer background, with hands-on experience in building data pipelines, performing transformations, and working with cloud-based data tools. The ideal candidate must have solid SQL skills, good understanding of data modeling, and hands-on exposure to DBT and cloud platforms (preferably GCP). Key Responsibilities: Build and maintain scalable ETL/ELT pipelines. Develop and enhance DBT models and transformations. Perform data cleansing, validation, and quality checks. Support cloud-based data engineering workloads (preferably GCP). Write optimized SQL queries for analytics and data processing. Collaborate with Data Engineers, Analysts, and Architects for requirement understanding. Monitor pipeline health, troubleshoot issues, and ensure data reliability. Document workflows, models, and mappings. Required Skills (Must Have) : Data Modeling understanding (Star/Snowflake). Strong SQL skills. Hands-on experience with DBT. Experience with at least one major cloud platform: GCP (BigQuery, Dataflow, Dataproc, Composer, GCS preferred) OR AWS / Azure equivalent services. Experience with data transformation and loading technologies. Good knowledge of Python for data tasks. Good to Have: PySpark or similar distributed data processing experience. Exposure to Airflow / Cloud Composer. Experience with Data Catalog / Dataplex (or similar metadata services). Familiarity with CI/CD, Git, and version-controlled workflows.