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Bengaluru metro and common Data Engineer title increase competition, but seniority and specific Airflow/Spark skills moderate density.
Core data engineering skills (Spark, AWS, Python) are highly transferable across industries.
Multiple explicit years and mandatory technologies (Spark, Airflow, AWS, Python) make shortlisting stringent.
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Lead design and maintenance of scalable big data infrastructure and processing pipelines handling billions of events daily.
Integrate and automate data ingestion, transformation, and augmentation from diverse sources ensuring data quality and platform performance.
Mentor and guide data engineering teams while collaborating cross-functionally to support product roadmaps and technical leadership updates.
Bachelor’s degree in Computer Science or related technical field.
8+ years of experience in designing and developing big data processing systems using distributed computing.
Strong expertise with SQL (6+ years), Python and Spark (5+ years), cloud platforms like AWS (6+ years), and Apache Airflow (4+ years).
Experience with NoSQL databases (DynamoDB), data modeling, and automation; proficiency in object-oriented programming and network protocols.
Experienced in building and optimizing complex, high-scale data architectures using cloud (AWS) and modern big data technologies (Spark, Airflow).
Comfortable operating in cross-functional teams collaborating closely with product, data, engineering, and operations units.
Skilled mentor with proven leadership in fostering high-performance, accountable teams focusing on continuous improvement and innovation.