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Tier-1 brand, popular data engineer role, mid-level seniority, and metro location increase applicant competition.
Core data-engineering skills transfer across industries, though payments/regulatory domain knowledge is beneficial.
No explicit years but required SQL and RDBMS expertise implies moderately strict technical screening.
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Design, implement, and maintain enterprise ETL data pipelines for global clients.
Optimize data processing using SQL and develop scalable code to handle large data sets efficiently.
Collaborate with peers and clients to deliver accurate, timely, and high-value data solutions across multiple projects.
Bachelor's degree in a quantitative field (BE/BTech); Master's preferred (ME/MTech).
Experience as a Data Engineer or similar role with strong data engineering concepts and methodologies.
Strong SQL skills and hands-on experience with Microsoft SQL Server and ETL frameworks.
Familiarity with Databricks and Spark is a plus; work experience required: Not explicitly mentioned in the JD.
Proficient in designing scalable data pipelines and optimizing database operations primarily using SQL and RDBMS technologies.
Capable of handling multiple projects and priorities with minimal supervision, demonstrating critical thinking and problem-solving skills.
Comfortable working with global teams across multiple time zones, maintaining quality and security compliance in data processes.