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Tier-1 brand, metro Bangalore, mid-level generalist data engineer, and broad skillset requirements.
Core data engineering technologies (Spark, Kafka, AWS, DBT) are broadly transferable across industries.
Explicit 5-8 years requirement plus long mandatory tech stack creates high shortlisting strictness.
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Design and build data infrastructure and systems including data pipelines, integration, and transformation to support efficient data processing and analytics.
Leverage big data technologies and cloud services, primarily AWS and Azure, to develop robust data solutions enabling actionable insights and informed decision-making.
Implement CI/CD frameworks alongside code repositories to automate and streamline data engineering workflows.
5 to 8 years of work experience in data engineering or related roles.
Mandatory skills include Big Data technologies, AWS (S3, Glue, EMR, Lambda, Kinesis), SQL, Python and/or Scala, Spark, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog.
Required education: Bachelor of Technology (B.Tech) or equivalent degrees such as M.Tech, M.E, MCA, B.E.
Experience with Snowflake and CI/CD frameworks is a significant advantage; proficiency in Microsoft Azure is expected.
Experienced in managing end-to-end data engineering pipelines within cloud environments, primarily AWS and Azure, supporting large-scale data analytics.
Capable of implementing automation and continuous integration/deployment processes to enhance data delivery and operational efficiency.
Comfortable working with diverse big data tech stacks, including real-time data streaming and orchestration tools like Kafka, Flink, and Airflow.