Optimize ETL/ELT pipelines using tools like DBT, Spark, or Airflow, bridging upstream (e.g. Debezium, MSK) and downstream processes. * Knowledge Sharing: the team on best practices, modern tools (e.g., Databricks, Snowflake, AI adaptation and integrations like Cursor/CodeRabbit), and cloud-native scalability. * Proven expertise in designing, developing & maintaining data lakehouses/DWH (e.g., Databricks Delta Lake, Snowflake) and transformations (e.g., DBT, SQL/Python/Spark). * Strong experience with cloud platforms such as AWS services (S3, Athena, MSK/Kafka, Terraform) and real-time streaming (e.g., Kafka, Spark Structured Streaming, Flink). * Hands-on knowledge of data governance tools (e.g., Unity Catalog, Collibra) for lineage, quality, catalogs, and SSOT. * Familiarity in AI/ML pipelines and MLOps (e.g., MLflow, feature stores) and complex system integration within modern data technologies.
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