Description

Responsibilities

• Architect, build, and maintain scalable data pipelines and ETL processes using modern tools and cloud technologies
• Develop and deploy data ingestion frameworks for structured and unstructured data sources.
• Work closely with data scientists, analysts, and DevOps teams to design efficient data models and ensure seamless integrations.
• Optimize performance of large-scale data lakes and warehouses.
• Implement data governance, lineage, and quality frameworks.
• Lead and mentor junior data engineers and ensure best practices in data engineering.

Qualifications

• 8+ years of hands-on experience in data engineering, ETL development, and pipeline automation.

Required Skills

• Strong expertise in at least one cloud platform - AWS, Azure, or GCP.
• Hands-on with Spark, PySpark, Databricks, Kafka, Snowflake, Airflow, SQL, and Python.
• Experience with data warehousing (Redshift, BigQuery, Synapse, etc.) and streaming technologies.
• Solid understanding of data modeling, orchestration, and performance tuning.
• Excellent communication skills and ability to work in collaborative, cross-functional teams.

Preferred Skills

• Experience in data modernization or migration projects.
• Familiarity with CI/CD pipelines and containerization (Docker/Kubernetes)

Key Skills

Education

Bachelor's degree