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Tier-1 brand, mid-level generalist data role in Bangalore with broad technical requirements increases candidate competition.
Strong Scala/Spark and Databricks emphasis increases domain specificity but skills remain moderately transferable.
Mandatory 5+ years plus Scala/Spark/Databricks and production SLAs make filters highly strict.
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Design, develop, and maintain high-throughput streaming and batch data pipelines processing billions of events daily using Spark Structured Streaming, Kinesis, and Databricks.
Own end-to-end pipeline lifecycle including ingestion, transformation, orchestration, and delivery ensuring data quality, observability, and SLA adherence.
Drive operational excellence through monitoring, alerting, incident response, cost optimization, and collaborate cross-functionally to evolve data platform and standards.
5+ years of data engineering experience building and operating large-scale production pipelines.
Strong programming skills in Scala (primary) and Python/PySpark.
Deep experience with Apache Spark (batch and Structured Streaming) and proficiency with Databricks platform including Delta Lake and Unity Catalog.
Location requirement: Bangalore, India. Bachelor's or master's degree in computer science, Information Systems, or equivalent industry experience.
Experienced in operating scalable, low-latency streaming data systems and large batch processing with strong focus on data quality and observability.
Demonstrates technical leadership in shaping pipeline architecture and automation with hands-on coding and infrastructure-as-code practices (Terraform).
Able to collaborate effectively with cross-functional teams to prioritize platform roadmaps and implement enterprise data governance standards.