Key Responsibilities

• Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data integration processes.
• Develop and optimize SQL queries, data models, and data structures for analytics and operational use cases.
• Work with diverse data storage systems, including relational, NoSQL, and distributed file systems.
• Implement data processing solutions using distributed computing frameworks such as Apache Spark or Hadoop.
• Collaborate with cross‑functional teams to deliver cloud‑native data engineering solutions on AWS or Azure.
• Develop automated workflows using orchestration tools such as Apache Airflow or Azure Data Factory.
• Apply DevOps practices including CI/CD automation, IaC, and containerization.
• Contribute to the design of resilient, scalable, and secure data architecture.

Requirements

• Experience: Minimum 3 years of professional...