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Tier-1 employer, metro location, and generalist data role give moderate applicant competition.
Core data engineering skills are broadly transferable across industries despite Steam Power domain context.
Multiple mandatory data engineering tools and seniority increase resume filtering strictness.
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Design, build, and maintain robust data pipelines and data lake architectures on Steam Datalake platform.
Develop and optimize data ingestion, cleaning, transformation, and feature extraction workflows including integrations with internal/external sources and APIs.
Lead workstreams autonomously, provide guidance to junior members, collaborate cross-functionally to develop analytical solutions and contribute to Generative AI use cases.
Bachelor's degree in Data Science, Computer Science, Computer Engineering, or equivalent experience.
Significant experience in data engineering and analytics including working with structured and unstructured databases.
Hands-on experience with databases like PostgreSQL and data warehousing tools such as Snowflake, Redshift, or Databricks.
Experience with ETL tools (Talend, Informatica), cloud platforms (AWS/Azure), data visualization tools (Tableau, Power BI), plus programming in Python/Scala/Java/SQL.
Experienced senior-level analytics engineer comfortable leading projects independently in fast-paced Agile environments.
Technical skillset bridging database architecture, ETL automation, cloud technologies, and data visualization with familiarity in AI/ML and prompt engineering.
Collaborative with product/business teams to translate requirements into effective analytical solutions and keen on reducing technical debt and driving efficiency.