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Remote role, common Data Engineer title, metro Hyderabad location, and broad Databricks skillset increase candidate competition.
Technical data engineering skills transferable across industries, though Databricks experience creates moderate domain specificity.
Mandatory 7+ years, Databricks and hands-on data engineering requirements raise strictness.
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Lead and mentor a team of data engineers while directly contributing to coding, architecture, and data platform development to support Journey Analytics initiatives.
Define and execute technical strategy for scalable, reusable data architectures and automated pipelines primarily using AWS Databricks.
Ensure data quality, governance, performance, and reliability of datasets for analytics and reporting through hands-on development and oversight.
7+ years of experience in Data Engineering.
Hands-on experience with AWS Databricks and developing/maintaining automated data pipelines.
Strong experience with GitHub version control workflows and legacy codebase refactoring.
Work Experience Required: 7+ years in Data Engineering. Other strict requirements or notice period: Not explicitly mentioned in the JD.
Experience leading data engineering teams with a mix of hands-on technical and people management skills.
Proven ability to design scalable, modular, and reusable data models and components for analytics use cases.
Comfortable working independently and driving initiatives in cross-functional environments with minimal supervision.