Data Engineer

3+ years building production-grade pipelines and data assets. Solid understanding (Intermediate) in layered/medallion architectures and entity modelling. Strong proficiency in SQL query tuning and optimization. 3-4 years using Python (or Scala) for production-grade transformations. Hands-on with at least one or multiple cloud platforms (AWS, GCP, or Azure). Practical experience with Athena, Redshift, BigQuery, Snowflake, or Databricks. 3+ years using orchestration frameworks (Airflow, MWAA, Dagster, etc.) and familiarity with CI/CD pipelines. Working familiarity and optimization with structured & semi-structured data. Proven experience implementing governance, access controls, and PII handling (Senior). 1–2 years experience with graph modelling and query optimization. 2–3 years experience with event-driven architectures (Kafka, Kinesis, Pub/Sub) for Senior roles. Strong ability to work cross-functionally; senior engineers also mentor and influence decisions.

Build and optimize BI-oriented dimensional models (star/snowflake) and ER data models. Support data models in a layered (medallion-style) architecture. Develop and maintain reliable, scalable ETL/ELT pipelines using SQL, Python/Scala, and orchestration tools. Implement validation frameworks, manage access controls, and handle PII data responsibly. Transform and optimize structured and semi-structured data and address schema evolution challenges. Apply graph database concepts for lineage, metadata, or relationship-driven use cases. Partner with analytics, product, and data science teams to translate requirements into robust datasets.