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Metro location, popular Data Engineer role, broad required skills, and a known Genpact brand increase competition.
Data engineering tooling and platform skills are moderately transferable across industries and domains.
Many mandatory technical skills (Azure, Databricks, Spark, ETL) but no explicit years requirement.
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Design, develop, and maintain data integration and provision pipelines for analytics and reporting teams.
Optimize and troubleshoot high-volume Spark job workflows and Databricks performance.
Implement scalable ETL workflows, Delta Lake features, data models, and CI/CD pipelines for batch and real-time processing.
Bachelor's or Master's degree in Business Analytics, Computer Science, Statistics, or Data Science.
Experience with Apache Spark, PySpark SQL, Delta Lake, Databricks, Azure DevOps or GitHub Actions for CI/CD.
Work Experience Required: Not explicitly mentioned in the JD.
Proficiency in English at C2 level.
Experienced in building and optimizing complex ETL data pipelines using Spark and Delta Lake in a hybrid cloud environment.
Able to design data models following medallion architecture and ensure data quality and scalability.
Comfortable collaborating with cross-functional teams and stakeholders to deliver data solutions aligned with business needs.