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Tier-1 brand, metro location, mid-level generalist data role with broad skill requirements increases competition.
Core data engineering skills are transferable, though payments domain knowledge slightly increases specificity.
Moderate strictness due to mandatory technical skills (SQL, RDBMS, ETL), but no explicit years requirement.
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Design, implement, and maintain enterprise ETL processes and scalable data pipelines for global clients.
Optimize SQL queries and develop efficient code to handle large data sets within multiple projects and industry sectors.
Collaborate with cross-functional teams to deliver timely, accurate, and robust data solutions while ensuring adherence to company policies and external regulations.
Bachelor's degree in quantitative field (Computer Science, Statistics, Econometrics, Engineering, Mathematics, Operations Research); ME/MTech preferred.
Experience as a Data Engineer or similar role with knowledge of data engineering concepts, data modeling, and database design.
Strong proficiency in SQL and relational databases, specifically Microsoft SQL Server; experience with ETL frameworks.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling multiple projects with differing priorities in a global, cross-time-zone environment.
Capable of critical thinking, innovation, and troubleshooting data issues with minimal supervision.
Familiarity with modern developer and productivity tools, eagerness to learn emerging technologies (e.g., Databricks, Spark, GitHub Copilot).