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Metro location and common Data Engineer title increase competition, seniority and niche skills moderate it.
Strong data-warehouse and semiconductor domain preference increases specificity, though core data engineering skills remain transferable.
Explicit 15+ year requirement plus mandatory data-warehouse, PySpark and AWS skillset creates strict filters.
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Lead complex data engineering projects involving design, build, and maintenance of secure, scalable data pipelines and analytics platforms.
Translate design requirements into technical data products working closely with Data Product Design teams.
Provide technical consulting, establish design standards, guide junior engineers, and evaluate data security access controls.
Experience with Data Warehouse design, including standards definition, framework building, and source-target mapping.
Strong programming skills in SQL and PySpark, and experience with AWS Cloud services including EMR, Redshift/Postgres.
Proven experience managing large, complex database projects handling high-volume data.
Work Experience Required: Minimum 15 years in data warehousing and related technologies.
Strong background in data warehouse architecture with skills in dimensional modeling and ERD design.
Experience in semiconductor or high-tech manufacturing domains.
Ability to produce high-quality technical documentation and problem-solving for performance tuning and root cause analysis.