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Tier-1 brand, mid-level data role, Bengaluru location, and broad skillset make competition high.
Core data engineering skills (Spark, SQL, Airflow, cloud) are readily transferable across industries.
Explicit 3+ years plus mandatory Spark, SQL, and cloud skills increases screening rigor.
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Develop and maintain automated data pipelines for ingestion, transformation, and delivery of analytics datasets.
Collaborate with data analysts, scientists, and product teams to understand requirements and support data flow across systems.
Contribute to data modeling, quality checks, validation, monitoring, and leverage AI-assisted tools to automate data tasks and improve productivity.
3+ years of experience in building and maintaining data warehousing and analytics solutions.
Hands-on experience with distributed data processing frameworks (Spark, Hive, or Iceberg) and proficiency in SQL for analytical workloads.
Working knowledge of Python, Java, or Scala for data transformations and pipeline development.
Experience with data pipeline orchestration tools (e.g., Airflow) and exposure to MPP analytical databases (Snowflake, Redshift).
Experienced in developing analytics-focused data infrastructure in large organizations.
Collaborates cross-functionally with analytics, product, and engineering teams and drives projects to measurable impact.
Familiar with AI agents or LLM-powered workflows integrated into data engineering and has strong software engineering fundamentals.