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About the Role
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 experience in data engineering, including at least 2 years working with cloud‑native data services. Programming: Proficiency in at least on...
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