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Tier-1 employer plus metro location and a popular data-engineering title increases candidate competition.
Core data engineering skills transfer across industries, though aerospace domain preferences moderately increase specialization.
Explicit 9+ years plus required PySpark, Databricks, ELT/ETL tools and data governance raises strictness.
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Design, develop, optimize, and maintain ELT/ETL data pipelines and processes for scalable data ingestion and transformation across various sources.
Implement data quality checks, governance, and master data management to ensure accurate and consistent data for business consumption.
Collaborate with global business and technology teams to understand problems, design scalable solutions, and maintain best practices in cloud environments.
Bachelor's in Data Science, Engineering, Mathematics, or Statistics with 9+ years relevant experience OR Advanced Degree with 5+ years relevant experience.
Minimum 2 years experience as a Data Engineer with proven design and implementation of data solutions.
Hands-on experience with ETL tools (e.g., Fivetran, SSIS, AWS Glue), Python, Pyspark, Databricks, and database technologies (SQL and NoSQL).
Strong proficiency with GitHub and Agile methodology; located in Bengaluru, India (Hybrid work setup).
Experienced data engineer with capability to build scalable, repeatable ETL/ELT pipelines in cloud platforms like Databricks.
Familiarity with data governance, master data management, and enterprise data architecture standards.
Comfortable working with cross-functional global teams in an agile setting and aligns with aerospace and defense domain processes (preferred but not mandatory).