Lead Functional Business Data Analyst

Lead Functional Business Data Analyst - Data Lake Assessment (Public Sector)

Location: Albuquerque, New Mexico (Flexible – Mid West/West Coast/Travel to New Mexico required 40-50% travel)

Employment: Full time employee of Speridian for a long-term contract

Visa Sponsorship: We cannot sponsor candidates who require Visa Sponsorship to work in the US.

Role summary

Lead the discovery and assessment of data and document sources across the environment department. Define requirements and the data model for a unified, searchable master index of regulatory records (permits, environmental assessments, inspections, compliance and enforcement records, and others). Serve as the bridge between program staff, external agencies and the technical team delivering a medallion-architecture (Bronze/Silver/Gold)

data platform, likely on Microsoft technology.

Key responsibilities

• Source discovery. Inventory source systems: permitting databases, legacy apps, SharePoint and file shares, scanned archives, GIS layers and spreadsheets. Document owners, volumes, formats, refresh frequency, quality and access constraints.
• Stakeholder engagement. Run workshops with program areas (air, water, waste, land, enforcement), records management, IT and partner agencies. Capture search use cases and personas such as internal staff, other agencies and the public.
• Master record definition. Define the "master document" entity and its metadata schema: document type, permit number, facility/site, applicant, location, program, status, issue and expiry dates, related records.
• Entity resolution rules. Define how facilities, permittees and sites are matched across systems
• Medallion layers. Map source-to-target for each layer: ability to define what lands in Bronze, the cleansing and conformance rules for Silver, and the search-ready model in Gold.
• Data quality. Profile data and produce a data quality assessment covering duplicates, missing keys, inconsistent codes and orphaned documents.
• Governance. Define a business glossary, reference data (document types, program codes, status values), data ownership and stewardship roles.
• Access and sensitivity. Identify confidential business information, PII, enforcement-sensitive records, retention schedules.
• Search requirements. Define search and discovery requirements: filters, full-text vs. metadata search, map-based search and relationships.
• Deliverables. Produce the current-state assessment, gap analysis, target-state recommendations, a phased roadmap and backlog/user stories for delivery.

Technology input. Support platform selection (see below Nice to have Microsoft ecosystem familiarity) with business criteria.

Required qualifications

• 8+ years as a business or data analyst, with at least 3 years leading data integration, data warehouse or data lake assessments or requirements.
• Strong data modeling literacy: conceptual and logical models, entity relationships, master and reference data concepts.
• Hands-on data profiling and analysis with SQL. Comfort with Excel; Python is a plus.
• Experience writing source-to-target mappings, data dictionaries and business glossaries.
• Proven facilitation of cross-departmental requirements workshops with non-technical stakeholders.
• Working knowledge of modern data platforms and medallion/lakehouse concepts.
• Excellent documentation and communication skills, including presenting findings to leadership.
• Experience defining master data management rules, including golden record, survivorship and match/merge logic.
• Experience applying data quality frameworks, including quality dimensions, metrics and scorecards.
• Experience analyzing unstructured data and defining document metadata requirements.
• Experience writing Agile user stories in Azure DevOps

Preferred / domain qualifications

• Experience in government environmental, natural resources, public health or other regulatory agencies.
• Environmental programs: familiarity with permit types such as air permits, NPDES/water discharge, stormwater, hazardous waste/RCRA, and environmental impact assessments. GIS literacy is also a nice to have
• Facility identifiers: familiarity with EPA's Facility Registry Service (FRS) or similar facility master data, which is very useful for cross-agency matching.
• Metadata standards: experience with document management and metadata standards, such agency taxonomy.

Nice to have Microsoft ecosystem familiarity

• Platforms: Microsoft Fabric (OneLake, Lakehouse, Data Factory/pipelines) and/or Azure Data Lake Storage Gen2 with Azure Databricks or Synapse.
• Governance: Microsoft Purview for data catalog, lineage, sensitivity labels and glossary.
• Search: Azure AI Search for document indexing and search.
• Document extraction: Azure AI Document Intelligence for pulling metadata from scanned or PDF permits.
• Reporting: Power BI.
• Document repositories: SharePoint / Microsoft 365, (existing documents hosted there today).