At Rowan Digital Infrastructure, we are transforming data center delivery for speed and scale. Our mission is to deliver best-in-class data center solutions to hyperscale customers who share our commitment to sustainability, and to do so with an unwavering focus on efficiency, quality, and flexibility. Our data center solutions are tailored to our customers’ needs and delivered by our exceptional end-to-end team. Rowan is assembling a strategic portfolio of data center sites in Tier 1 markets across the United States at various stages of development, and we’re looking for incredible and passionate people to help us advance our company and our commitment to building a more sustainable future.

Rowan is backed by Quinbrook, a leading investor in the energy transition, and Blackstone, the world’s largest alternative asset manager.

Ready to join us in transforming the future of data centers and sustainability? Apply now to explore exciting career opportunities at Rowan Digital Infrastructure and be a part of our mission to revolutionize data center delivery.

Role Summary

The Data Engineer, Operations Analytics builds the data platform, pipelines, data standards, and quality controls that make the team’s data reliable. Working alongside the Data Scientist, this role owns the data from the agreed handoff point through to curated, analysis-ready tables. The role reports to the Director, Operations Analytics.

This role partners closely with the Data Scientist, IT, vendor partners, Operations, and Compliance to make sure reliable data is in place before the first turnkey solution in mid-2027, which will add new data sources and users. As the team grows, it also gives the Reporting Lead and Business Analysts documented standards and curated tables to build on. As a second owner of the analytics workspace, the position reduces dependence on any one person, keeps the platform supportable through shared change control and documentation, and supports audit readiness. It also prepares and governs data for AI and language model use cases.

Travel: Ability to travel up to 25% for company gatherings or to project sites.

Location: Denver, Colorado (3-day hybrid in-office role)

Compensation: $108K - $125K (Offers Bonus)

Essential Responsibilities

Build and evolve the team’s data platform on Azure and Databricks, including ingestion, storage, and curated layers

Govern the workspace through Unity Catalog, including catalog and schema design, permissions, lineage, and data classification, so access is controlled and auditable as new users and data sources come online

Own ingestion into Databricks from the agreed handoff point with vendor partners and IT, and review upstream building and facility data platform work

Design, build, test, and monitor production pipelines for power, cooling, equipment, and monitoring data, and scale them as new data sources and users come online

Define and maintain a reference data standard and data dictionary, including consistent naming for sites, assets, equipment, and vendors, documented so new team members can onboard quickly

Build data quality checks, monitoring, alerts, and runbooks so issues are detected and resolved quickly

Publish and maintain curated tables that serve models, Tableau scorecards, and KPIs so every report and model draws on the same trusted data

Partner with the Data Scientist to build and maintain Genie spaces and LLM-powered tools, including the curated tables, metadata, table and column descriptions, and certified queries they depend on

Prepare and maintain data for AI and language model use cases, such as document and text ingestion, vector search indexes, and retrieval pipelines, held to the same quality and change control standards as other production data

Serve as second owner of the Databricks workspace and co-own change control with the Data Scientist, including code review and separate development and production environments

Partner with the Data Scientist, Operations, Reliability, Engineering, and IT teams, and with the Reporting Lead and Business Analysts as they join, to align data structures with modeling, reporting, and operational needs