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Senior, niche Big Data role in Bangalore with specialized stack reduces applicant density.
Strong data engineering skills transfer across industries, though enterprise DWH experience favors similar domains.
Explicit 10–14 years requirement plus mandatory Big Data, cloud, and DWH skills makes filtering strict.
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Design, build, and scale data pipelines and modern data warehouse platforms (batch + real-time) to support enterprise reporting, BI, and analytics across large datasets.
Lead technical architecture, enforce best practices in data engineering, coding standards, and cloud infrastructure (AWS preferred).
Mentor engineers, conduct design/code reviews, and collaborate with product, analytics, and engineering teams to deliver reliable data solutions.
10–14 years of experience in software/data engineering with proven track record of impact.
Strong expertise in Big Data ecosystems (Spark, Hadoop) and proficiency in SQL, Python/Scala/Java for data processing.
Hands-on experience with cloud platforms (AWS preferred) including EMR, Glue, S3, Lambda.
Experience with data modeling, warehousing, distributed systems, and enterprise DWH systems for reporting and analytics.
Experienced in scaling and optimizing large, complex data pipelines and warehouse architectures with a focus on reliability and performance.
Capable leader in technical architecture and team mentorship within multi-disciplinary teams (product, analytics, engineering).
Comfortable working in a high-scale, fast-growing automotive and marketing data environment with emphasis on cloud and big data technologies.