We are looking for a skilled and detail-oriented ETL Data Engineer to design, build, and maintain robust and scalable data extraction, transformation, and loading (ETL) pipelines. The ideal candidate will work closely with data analysts, scientists, and business stakeholders to deliver high-quality data solutions that support operational reporting, analytics, and decision-making. Description for Internal Candidates  Key Responsibilities: Design, develop, test, and maintain ETL pipelines to process structured and unstructured data from diverse sources using Azure services such as cloud functions, data factory, databricks and other streaming services. Collaborate with data architects and business teams to gather data requirements and ensure data accuracy, integrity, and consistency. Optimize ETL workflows for performance, reliability, and scalability. Develop and maintain data models, schemas, and documentation for ETL processes. Monitor data flows and troubleshoot issues in production environments. Implement and enforce data quality rules, validation checks, and exception handling. Work with cloud and on-premise data storage systems and integrate them as needed. Ensure compliance with data governance, security, and privacy standards. Required Qualifications: 3–7 years of experience in ETL development and data engineering. Proficiency in Azure cloud functions, Azure Data Factory. Strong SQL skills and experience working with relational databases (e.g., SQL Server, Oracle, PostgreSQL). Experience in scripting languages such as Python, Shell, or Scala for data manipulation and automation. Solid understanding of data modeling, warehousing concepts, and big data platforms. Experience with version control and CI/CD tools (e.g., Git, Jenkins). Ability to work independently and in cross-functional teams. Originally posted on Himalayas