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Tier-1 employer, metro location, mid-level generalist role, and broad skill requirements drive high competition.
Core data engineering skills transferable across industries, but Snowflake/dbt focus makes fit moderately sensitive.
Explicit 4–8 years plus mandatory Snowflake, dbt, Python, and orchestration tools imply high shortlisting strictness.
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Develop, maintain, and optimize scalable data pipelines and transformations for analytics, reporting, and operations.
Ensure data quality through testing, documentation, and monitoring within the data platform ecosystem.
Collaborate with engineers, analysts, data scientists, and stakeholders to deliver reliable and well-governed data solutions.
4-8 years of experience as a Data Engineer or similar role.
Mandatory hands-on experience with Snowflake including SQL, modeling, and optimization.
Proficiency in SQL, Python, dbt (or similar), and orchestration tools like Airflow, Dagster, or Prefect.
Work model is Hybrid with a requirement to work 2 days per week from an HPE office.
Experienced in modern data platform architectures including batch and streaming data pipelines and cloud environments (AWS, GCP, or Azure).
Skilled in data modeling, pipeline automation, and implementing DataOps practices such as CI/CD and monitoring.
Able to translate business requirements into technical data solutions and collaborate effectively with cross-functional teams including senior engineers and data scientists.