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Mid-level metro role with broad skills, popular data-engineering title, and moderate brand visibility.
Technical data engineering skills are transferable, though platform/tooling and data-product experience increases domain specificity.
Explicit 5+ years, lead experience, and multiple mandatory technical skills make shortlisting stringent.
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Lead a cross-functional team to build and maintain data engineering platforms and data pipelines, owning architecture and delivery end-to-end.
Manage day-to-day team operations including scrum ceremonies, sprint planning, and backlog management while mentoring team members.
Drive platform stability, DevOps capabilities, and contribute to community-of-practice initiatives including onboarding, upskilling, and data product ownership.
Bachelor's degree or higher in Computer Science, Statistics, Business, IT or related field.
5+ years in data engineering or related discipline with at least 2 years in a technical lead/team lead role.
Proficiency in Python, advanced SQL, intermediate cloud (Azure/AWS/GCP) and DevOps including CI/CD pipeline ownership.
Experience with data modelling, data warehousing concepts, data quality frameworks, and Agile methodologies.
Experienced in delivering enterprise-scale data solutions with modern tools such as Dagster, dbt, and Snowflake, with strong data product knowledge including lineage and certification.
Capable of leading technical design decisions and mentoring engineers, bridging technical and business communication effectively.
Comfortable working in fast-paced environments, driving continuous improvement, innovation, and cross-team collaboration.