Data Architect Jobs

About The Position

Requirements

• Experience Baseline: 8+ years of comprehensive enterprise data integration, data warehousing, or data architecture experience.
• Government Depth: 3+ years of dedicated, hands-on data integration experience working inside a federal, state, or local government framework.
• NIEM Mastery: Documented, verifiable experience designing and executing NIEM-conformant or NIEM-compatible information exchanges.
• Domain Architecture: Advanced structural familiarity with NIEM domains, data components, exchange specifications, and extension rules.
• Mapping Expertise: Extensive background executing complex source-to-target mapping, data profiling, metadata logging, and data-lineage cataloging.
• Exchange Protocols: Proven experience managing both structured and semi-structured data-exchange formats, including JSON, XML, REST APIs, CSV flat files, database views, and automated batch/SFTP pathways.
• Data Quality Engineering: Strong track record establishing automated cross-system data reconciliation scripts and automated validation profiling rules.
• Vetting & Location: Must be a U.S.-based citizen or resident. Must be able to successfully clear an FDLE Level II background screening (including fingerprinting) within 5 business days of contract award.

Nice To Haves

• Direct experience integrating or mapping data from legacy state financial and procurement architectures.
• Working data domain familiarity regarding procurement workflows, contract activities, purchasing cards, state vendor payments, or grant management ledgers.
• Hands-on data engineering experience leveraging Azure Databricks workspaces and Azure Data Lake Storage Gen2 (ADLS Gen2).
• Deep technical specialization in master data management (MDM) or advanced programmatic entity resolution.
• Working knowledge of secure government interoperability models or federated identity standards beyond basic NIEM implementations.

Responsibilities

• NIEM Compliance Ownership: Lead the structural strategy for NIEM compliance and compatibility, detailing exact plans for NIEM conformance levels, component reuse, domain extensibility, and constraint mitigation.
• Canonical Modeling: Define, build, and maintain the platform's canonical data model to standardize information formatting across all ingested state datasets.
• Cross-System Mapping: Develop a unified cross-system mapping and standardization framework to reconcile critical field differences, schema variations, timing misalignments, and data quality gaps across legacy source systems.
• Entity Resolution: Design and implement record-linkage models and identifier normalization logic to accurately track unique vendors and transactions across completely separate agency databases.
• Source Coordination: Act as the primary technical point of contact for source-system data owners across different state departments to resolve field clarifications, mapping guidance, and legacy database nuances.
• Documentation Delivery: Produce comprehensive data dictionaries, transformation documentation, source-to-canonical lineages, and highly detailed data-exchange specifications in open, editable formats.
• Onboarding Optimization: Map out and support the ingestion pipelines for core procurement modules, including invoices, purchase orders, contracts, vendor information portal ledgers, and downstream financial fields.
• Reusable Patterns: Build reusable, automated data-mapping templates to accelerate and standardize the onboarding workflows for the initial wave of 8–10 state agencies.

Benefits

• culture of success
• chance to work on revolutionary federal IT infrastructure
• opportunity to grow alongside cutting-edge technology
• promoting from within