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Metro Bengaluru location and common Databricks/Spark data engineer profile create moderate applicant competition.
Core data engineering skills are transferable across industries, with domain knowledge as a nice-to-have.
Explicit 6–8+ years plus mandatory Databricks, Spark, SQL, Python, and cloud skills create strict filters.
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Design, build, and maintain scalable ETL/ELT data pipelines and models on Databricks/Spark supporting AI/ML and analytics use cases.
Develop production-grade data models, optimize pipeline reliability, cost, and performance while ensuring data quality and governance.
Collaborate cross-functionally with architects, data scientists, product teams; mentor junior engineers and drive engineering best practices.
6-8+ years of experience in Data Engineering with production-grade data platform development.
Advanced proficiency in SQL and Python; hands-on experience with Databricks, Apache Spark, and ETL/ELT pipeline orchestration tools.
Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent experience.
Must be based in Bengaluru; experience with cloud platforms (AWS/Azure/GCP) and data lake/lakehouse architectures.
Experienced in building end-to-end data solutions for analytics and AI/ML contexts, particularly with batch-first, scalable pipelines.
Skilled in data modeling techniques (fact/dimension, SCDs, CDC) and producing AI/ML consumable datasets.
Strong collaborator comfortable translating ambiguous requirements into reusable data assets and mentoring peers in a fast-growing global tech environment.