Data Platform Engineering Manager
$150k - $175kRed Oak Technologies
Job Description
Title: Data Platform Engineering Manager
\nLocation: Golden, Colorado
\nPosition: Fullitime On site
\nBase Salary: $150-175K
\n \nJob Profile Summary
\n \nThe Data Platform Engineering Manager (Governance & Quality) leads the strategy, stability, governance, and adoptionof the organization’s modern data platform. The role is responsible for ensuring the data ecosystem supports scalable, reliable, and business-impacting analytics capabilities. This position works cross-functionally with business stakeholders, data engineering, analytics teams, and IT leadership to guide platform direction, drivebest practices, and ensure stronguser adoption. It is a player-coach role that blendsplatform architecture oversight, operational ownership, and enablement of self-service analytics across the organization.
\n \nJob Description
\n \nRoles & Responsibilities:
\n \nPlatform Strategy & Architecture
\n \n- \n
- Execute and deliver against the data platform roadmap aligned to business and analytics strategy. Contribute to and implement architectural decisions related to data ingestion, transformation, modeling patterns, Lakehouse architecture, medallion design, and Semantic and consumption layer strategy across Power BI and Sigma. \n
- Ensure platform scalability, performance, cost optimization, and future-readiness. \n
- Provide strong inputfor and introduce new platformcapabilities, tooling, and automation to improve platformmaturity. \n
Platform Stability & Operations
\n \n- \n
- Manage platform reliability, availability, and performance monitoring. \n
- Establish and manage SLAs / SLOs for data pipelines and analytics workloads, incident management and root cause processes, platform governance, security, and access patterns. \n
- Partner with infrastructure / cloud teams and provideinput on environment strategy, workspace management, cost visibility and optimization. \n
- In coordination with Data &Analytics leadership, ensuredata platform production readiness standards for data productsand pipelines. \n
Adoption & Enablement
\n \n- \n
- Support adoption of the data platform and self-service analytics capabilities \n
- Define standards for data product design, dashboard and analytics development, documentation and discoverability. Lead userenablement initiatives such as trainingprograms, office hours and communityof practice, analyticsgovernance forums. \n
- Partner with businessteams to identifyhigh-value use cases and accelerate delivery. \n
Team Leadership & Delivery
\n \n- \n
- Lead and developa team of data engineers, analytics engineers, or platform specialists. \n
- Establish delivery frameworks and prioritization processes. \n
- Promote modern engineering practicesincluding CI/CD for data pipelines, Testing and observability, Agile / product-oriented operating models. \n
- Collaborate closely with Data & Analytics leadership to ensure platforminvestments drive measurable business outcomes. \n
Education:
\n \n- \n
- Bachelor’s degree in Engineering, Computer Science, Data Science or Information systems or equivalent work experience. \n
Experience:
\n \n- \n
- 7+ years of experience in data engineering, analytics engineering, or data platformleadership \n
- 3+ years of experience leadingtechnical teams \n
- Hands-on experience with Databricks / Lakehouse architectures \n
- Strong familiarity with modern BI and semanticconsumption patterns (PowerBI, Sigma, or similar) \n
- Experience managing production data platforms in cloud environments (Azure, AWS, or GCP) \n
- Proven ability to drive platformadoption and organizational change \n
- Strong stakeholder engagement and communication skills \n
$150k - $175k
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