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Tier-1 brand plus a common Data Engineer mid-level profile increases applicant competition significantly.
Core data engineering skills (ETL, SQL, pipelines) are broadly transferable across industries.
Moderate technical and education requirements (SQL, RDBMS, ETL, degree) create medium strictness.
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Design, implement, and maintain enterprise ETL processes and data pipelines for a global client base.
Use SQL and database technologies to optimize large data set processing and develop scalable code.
Collaborate on multiple projects to deliver accurate, high-value data solutions, ensuring quality through best practices like code reviews and data validation.
Degree: BE/BTech in quantitative field mandatory; ME/MTech preferred.
Experience: Data Engineer or similar role with strong data engineering concepts, data modeling, and database design experience.
Strong skills in SQL and relational databases, specifically Microsoft SQL Server.
Familiarity with ETL frameworks and ability to maintain data pipelines; experience with Databricks and Spark is a plus.
Experienced in managing data engineering projects supporting scalable data solutions across multiple industries and clients.
Comfortable working in a global, multi-time zone environment handling competing priorities and multiple projects.
Demonstrates curiosity about new developer tools and can analyze, troubleshoot data issues with minimal supervision.