Position SummaryIQ Fiber is seeking a Manager, Enterprise Data Management responsible for the company's master data management (MDM) platform and the data governance program around it, across our growing fiber-to-the-home (FTTH) expansion markets. Master data is the foundation the business builds on-the parcels we evaluate, the addresses we serve, the customers we connect, and the network we operate-and this role owns that foundation: the platform that holds it, the governance that keeps it trustworthy, and the assurance that every team has the data they need to do their best work.
This role partners with leaders across Engineering, Construction, Commercial, Network Operations, Finance, and Support to define how data is owned and governed and to turn it into information the business can act on with confidence. It carries broad authority over how the company's foundational data is defined, works closely with a small delivery team on the in-house platform, and maintains high visibility with senior leadership.
Location: Jacksonville, FL preferred; hybrid or remote considered
Essential Duties and Responsibilities- Own the MDM platform roadmap, backlog, and priorities; make the tradeoff calls; and take part in architecture and design reviews, including sequencing technical debt against feature work.
- Discover what stakeholders and data consumers across the business need, translate that into requirements, and validate that what is delivered meets them.
- Coordinate delivery with the team that builds and maintains source integrations and platform features, keeping releases moving on a predictable cadence.
- Own the company-wide data governance framework for the core data domains: parcel, address, customer, service, and network.
- Establish and maintain data ownership across the organization-defining which system is authoritative for which attribute, documented, versioned, and agreed-building consensus with source system owners, including the Manager, GIS, and escalating decisions that need senior leadership input to the sponsors.
- Own the rules that turn source data into trusted golden records, including attribute mapping, authority, and identity resolution and matching.
- Run structured working sessions with system owners, data stewards, and platform maintainers to agree the governance rules for each source, then verify the results against live data.
- Define data quality standards, monitor performance against them, and partner with system owners to raise quality at the source.
- Ensure changes flowing back to source systems are governed, audited, reversible, and human-approved.
- Establish data stewardship as a routine function-defining the roles, daily queues, service expectations, and escalation path-and enable stewards and consumers with the training and documentation that keeps the program durable through role changes.
- Serve data consumers across Commercial, Design, Network Operations, Finance, Support, and OSP-including downstream analytics and reporting-with clean, well-documented data products, and onboard new data sources as the business adds capabilities and enters new markets, including markets added through acquisition.
- Define and report the measures that show data health and program progress, in terms the business cares about.
Required Qualifications- Bachelor's degree in a relevant field, or equivalent experience.
- 6+ years in data product management, data governance, master data management, business systems analysis, or a closely related discipline.
- Demonstrated ownership of a data platform, data product, or governance program from requirements through adoption, including establishing the ownership models, stewardship roles, quality standards, and operating rhythm that sustain it.
- Strong understanding of master data concepts: golden records, survivorship and authority rules, entity resolution and matching, deduplication, lineage, and audit.
- Working understanding of data architecture: relational and spatial data modeling, schema design and normalization tradeoffs, ETL and ELT patterns, and when synchronization should be batch rather than event-driven.
- Experience integrating and reconciling data across multiple operational systems, including REST APIs, webhooks, and event-driven or queue-based sync, and the failure modes that come with them (idempotency, retries, ordering, and reconciliation when a write-back fails partway).
- Familiarity with modern application development practices-version control, code review, CI/CD, environment promotion, and release management-enough to take part in a design review, judge technical debt honestly, and follow what an integration is doing in the code.
- Fluency in SQL and the habit of working directly with data rather than relying on summaries.
- Excellent written communication, including documenting a decision so that it survives turnover and putting a clear recommendation in front of senior leadership.
- Ability to build alignment among stakeholders who do not report to you-across Engineering, Construction, Commercial, and Network Operations-and to make a decision and see it adopted.
- Ability to handle sensitive and confidential information, including PII, with sound judgment and integrity.
- Proficiency with Microsoft 365.
- Experience in telecommunications, utilities, broadband, or infrastructure development a plus.
- Familiarity with geospatial or location data, and with parcel and address data in particular, a plus.
- Exposure to platforms such as ArcGIS and Vetro FiberMap, an ISP billing or OSS/BSS system, or an address verification service a plus.
- Experience with commercial MDM or data governance tooling such as Profisee, Informatica, Reltio, Collibra, or Alation a plus.
- Working knowledge of Python (the language the platform is built in) a plus.
- Experience with a modern analytics stack such as Snowflake, dbt, or Sigma a plus.
- Experience building a data program in a high-growth, multi-market environment, including integrating data from acquisitions, a plus.
- Certification such as CDMP, DGSP, or a recognized product management credential a plus.
- Other duties as assigned.
What Success Looks Like- Teams across the business work from one trusted source for parcel, address, customer, and service data, and trust it enough to make decisions on it.
- Data ownership is clear: every core attribute has a named authoritative system and a named accountable owner, documented and agreed across the organization.
- Data stewardship runs as a routine function, with daily queues worked to a known service level, and governed changes reach source systems accurately and safely-every one audited, reversible, and human-approved.
- Data quality is measured and improving, market over market, as the footprint grows.
- New sources and newly acquired markets are onboarded on a repeatable path, and the data foundation actively supports building and delivering great networks to our customers.
- Senior leadership has clear, current visibility into data health and program progress.
