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Tier-1 employer, metro location, mid-level generalist role with broad skills increases candidate competition.
Skills are transferable across industries, but specialized big-data tooling creates moderate domain bias.
Explicit 5-8 years requirement plus wide mandatory tech stack increases shortlisting strictness.
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Design and develop robust data infrastructure and pipelines using big data and cloud technologies to support efficient data processing and analysis.
Implement and manage data integration, transformation solutions, and CI/CD frameworks in collaboration with code repositories like GitHub.
Leverage technologies including Spark, Scala/Python, Kafka, Airflow, DBT, Flink, Apache Iceberg, and AWS services to enable actionable business insights.
5-8 years of work experience in data engineering or related roles.
Mandatory skills: Big Data, AWS (including S3, Glue, EMR, Aurora Postgres, Lambda, Kinesis), SQL, Python or Scala, Spark, Kafka, Airflow, DBT, Flink, Apache Iceberg, Datadog, and CI/CD implementation experience with a repository like GitHub.
Educational qualification: Bachelor of Engineering or equivalent (B.Tech, M.Tech, M.E, MCA).
Work Experience Required: 5-8 years.
Experienced in building scalable data solutions with a strong command of big data ecosystems and AWS cloud technologies.
Proficient in programming with Python/Scala and working knowledge of data orchestration and streaming tools like Airflow, Kafka, and Flink.
Capable of implementing and managing end-to-end data pipelines and CI/CD frameworks in advisory or client-facing environments.