Key Responsibilities:

• Lead design and development of end-to-end data pipelines (batch and streaming) using modern technologies.
• Architect and maintain cloud-based data platforms (e.g., AWS, Azure, GCP).
• Develop and optimize ETL/ELT processes to ingest data from various internal and external sources.
• Implement data governance practices including data quality, cataloging, and lineage.
• Collaborate with business and analytics teams to understand data requirements and deliver high-quality datasets.
• Mentor junior engineers and provide technical leadership on data projects.
• Drive best practices in data engineering, DevOps, and CI/CD pipelines.
• Ensure scalability, performance, and cost-efficiency of data platforms.

Required Skills & Experience:

• 8+ years of experience in data engineering or related fields.
• 3+ years of experience in a lead or senior-level role.
• Strong proficiency in Python, SQL, and Spark.
• Experience with cloud platforms like AWS (S3, Redshift, Glue, EMR), Azure, or Google Cloud (BigQuery, Dataflow).
• Deep knowledge of data modeling, warehousing (Snowflake, Redshift, BigQuery), and performance tuning.
• Experience with streaming technologies (Kafka, Kinesis, Flink).
• Familiarity with orchestration tools (Airflow, Prefect, Dagster).
• Exposure to infrastructure as code (Terraform, CloudFormation) and containerization (Docker, Kubernetes).
• Strong understanding of data privacy and compliance (e.g., GDPR, HIPAA).