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Strong employer brand, metro location, and broad generalist data skillset increase applicant competition.
Core data engineering skills transfer across industries, though governance and CAO domain knowledge add specialization.
Mandatory 7+ years and specific SQL/Python, cloud, data governance, and automation requirements create strict filters.
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Build and support scalable data products including data streams, schemas, APIs, and automation workflows to improve operational capacity and decision-making.
Translate ambiguous business problems into practical, production-ready technical solutions across multiple systems and domains.
Lead and contribute to engineering standards, reusable patterns, and mentor team members in AI-assisted development tools and modern engineering practices.
Minimum 7 years of experience in data engineering, analytics engineering, software engineering, automation engineering, or related technical fields.
Strong proficiency in SQL and Python with experience building reliable data pipelines, data models, APIs, and automated workflows.
Experience with cloud data platforms, data warehouses, orchestration tools, Git-based development, and CI/CD practices.
Bachelor’s degree or equivalent experience in Computer Science, Data Engineering, Information Systems, or a related field.
Experienced in leading complex technical initiatives involving multiple systems, business domains, and collaborators with strong product thinking.
Demonstrates deep expertise in data quality, governance, security, access controls, and production reliability.
Proficient in leveraging AI-assisted development tools and large language models to enhance engineering productivity while ensuring quality control.