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Data Architect

2 weeks ago

Greenwood Village, Colorado, United States Skills 5 Inc Full time

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Job Title: Data Architect

Job Location: USA, East Coast (or) Remote - willing to work in EST timings

Job Summary:

We are seeking an experienced Data Architect to design and build the unified data model supporting our Operational Data Store (ODS) initiative. This is a working architect role requiring both strategic data modeling expertise and hands-on technical execution. The ideal candidate will bridge domain-level data ownership (Data Mesh principles) with enterprise-wide integration (Data Fabric patterns), creating a unified data layer that respects source system context while enabling cross-domain analytics and operations. This role requires someone who can define the architectural vision while personally building data models, writing transformation logic, and validating implementations against source systems. This is a remote, work at home opportunity in the US.

Key Responsibilities:

Design and build the unified data model for the Operational Data Store, balancing domain-specific context with enterprise integration requirements.

Define the architectural approach for federating domain data products into a cohesive enterprise data layer without creating monolithic dependencies.

Develop data transformation specifications, mapping rules, and working examples that preserve domain semantics while enabling cross-domain consistency.

Establish canonical data models that integrate across domain boundaries while respecting source system ownership and business context.

Perform source system analysis, data profiling, and gap assessments to understand domain data products and their integration requirements.

Write and validate SQL queries, transformation logic, and data quality rules to prove out architectural decisions before handoff.

Define system of record ownership across domains and maintain accurate data lineage documentation for federated data sources.

Design integration patterns that allow domains to evolve independently while maintaining enterprise data consistency.

Collaborate directly with Data Engineers during implementation, troubleshooting data quality issues and refining transformation logic.

Partner with domain stakeholders and enterprise architects to align domain data products with cross-domain analytics and operational needs.

Establish federated data governance standards that balance domain autonomy with enterprise consistency requirements.

Conduct architecture reviews focusing on data integrity, performance optimization, and scalability of the ODS.

Ensure compliance with data privacy regulations, security standards, and audit requirements in financial services.

Stay current with industry trends in Data Mesh, Data Fabric, and regulatory changes in the FinTech sector.

Required Qualifications:

  • Bachelor's or master's degree in computer science, Information Systems, Data Science, or related field.
  • 10+ years of experience in data management with at least 5+ years in data architecture roles.
  • Strong understanding of Data Mesh principles (domain ownership, data as product, federated governance) and Data Fabric concepts (unified access, integration layer, cross-domain visibility).
  • Proven expertise in logical and physical data modeling using tools such as ERwin, PowerDesigner, or similar.
  • Experience designing canonical data models that integrate multiple domain data sources while preserving business context.
  • Strong hands-on SQL skills with ability to write complex queries for data profiling, validation, and transformation.
  • Experience building Operational Data Stores, data warehouses, or enterprise data hubs with multiple source system integrations.
  • Demonstrated ability to perform data profiling, source system analysis, and data quality assessments independently.
  • Hands-on experience developing data transformation specifications and mapping documentation that engineers can implement.
  • Working knowledge of ETL/ELT patterns and data pipeline architecture.
  • Familiarity with event streaming platforms (Kafka, Kinesis) for real time data ingestion scenarios.
  • Solid understanding of data governance, metadata management, and data lineage practices.

Preferred Qualifications:

  • Demonstrates judgment and flexibility - positively deals with shifting priorities and rapid change of environments.
  • Experience in financial services, insurance, or large scale enterprise data platforms.
  • Experience implementing Data Mesh architectures or federated data governance models.
  • Proficiency with Python or similar scripting language for data analysis and validation.
  • Familiarity with cloud data services (AWS Glue, Azure Data Factory, Snowflake, Databricks).
  • Knowledge of data catalog and lineage tools (Collibra, Alation, Apache Atlas).
  • Exposure to domain-driven design principles applied to data architecture.
  • Understanding of regulatory requirements (SOX, GDPR, CCPA) as they apply to data management.
  • Experience mentoring Data Engineers and establishing team technical standards.