Data Engineering Lead

CareMore Health•US-Texas-Remote, TX
•$113,346 - $178,968

About The Position

Owns the design and delivery of enterprise data platform capabilities for assigned domains, acting as the primary technical authority for data engineering architecture and standards. Leads complex data platform initiatives, sets engineering direction, and drives the maturity of data infrastructure across the organization. The IT Data Engineering Lead is a recognized subject-matter expert who operates with minimal supervision and is the primary point of accountability for an area of IT data engineering work. Decisions impact function-wide results. This job proactively addresses undefined problems, makes recommendations that influence functional strategy, and synthesizes input across multiple stakeholder groups.

Requirements

  • Recognized subject-matter expert in data engineering.
  • Operates with minimal supervision.
  • Primary point of accountability for an area of IT data engineering work.
  • Ability to address undefined problems.
  • Ability to make recommendations that influence functional strategy.
  • Ability to synthesize input across multiple stakeholder groups.

Responsibilities

  • Lead the design and delivery of enterprise data platform initiatives, setting architectural direction and owning technical quality from design through production.
  • Define engineering standards, data modeling practices, and platform governance frameworks for data engineering.
  • Serve as the primary technical authority for data platform design decisions, advising IT leadership and data architects.
  • Drive data platform modernization and cloud adoption efforts, developing strategic recommendations for senior leadership.
  • Own vendor and tool relationships for core data engineering platforms, managing roadmap alignment and escalations.
  • Identify data architecture gaps, technical debt, and improvement opportunities, developing actionable recommendations.
  • Mentor senior data engineers and build technical capability across the data engineering team.
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