10+ years of overall experience in data engineering and architecture, with at least 5 years as a lead or architect.
Deep expertise in native cloud data services on AWS (e.g., Glue, Redshift, Athena, EMR), Azure (e.g., Synapse, Data Factory, Delta Lake), and GCP (e.g., BigQuery, Dataflow, Pub/Sub).
Strong understanding of data integration, streaming (Kafka, Kinesis, Pub/Sub), and real-time analytics.
Hands-on experience with Databricks and Snowflake including performance optimization, data sharing, and governance features.
Knowledge of emerging trends such as:
Data Lakehouse architecture (Delta Lake, Apache Iceberg)
Data Mesh
Generative AI for data preparation & metadata management
ML-powered data quality and observability tools (e.g., Monte Carlo, Soda, Great Expectations)
Modern catalog and governance platforms (e.g., Unity Catalog, Collibra, Alation)
Proficiency in data modeling, metadata design, and security architecture (e.g., row-level security, data masking).
