Key Responsibilities

• Design and develop scalable data pipelines to ingest, transform, and process large-scale datasets
• Build and maintain data orchestration workflows to support reliable data movement across systems
• Extract and integrate data from multiple sources including databases, APIs, and cloud storage systems
• Transform raw data into structured, high-quality, and consumable data assets for analytics and reporting
• Develop and maintain logical and physical data models including warehouse and data mart structures
• Define and manage relational schemas, primary/foreign keys, and stored procedures
• Perform data quality checks, validation, and cleansing to ensure accuracy and consistency
• Develop and optimize data flows for performance, scalability, and reliability
• Write production-grade code for data processing using Python, Java, or Scala
• Build and execute test cases to validate data pipelines and transformations
• Deploy and monitor data engineering solutions in production environments
• Contribute to documentation, code standards, and operational playbooks
• Collaborate with cross-functional teams to translate business requirements into technical solutions
• Identify and recommend appropriate analytical and data engineering approaches for business problems
• Support data governance practices and ensure compliance with data policies and standards
• Work on continuous improvement of data systems, architecture, and performance