Role Description CORMAC is seeking a Data Architect to be responsible for designing, implementing, and governing the enterprise data architecture for a cloud-based CMS program supporting large-scale data ingestion, transformation, analytics, metadata management, and user access through platforms including Databricks, online portals, and metadata catalog solutions. Ensures data is structured, secured, governed, and optimized to support reporting, analytics, interoperability, and regulatory compliance across the enterprise. This position will be tasked with helping in the delivery of solutions for our clients so we are seeking a hands-on technical leader with broad technical experience and deep, narrowly focused data expertise (e.g. data analytics, data engineering, Cloud, etc.). - Design and maintain enterprise data architecture for structured, semi-structured, and unstructured data across cloud-based platforms and data lake/lakehouse environments - Define data models, data standards, naming conventions, and master data management strategies to support enterprise-wide consistency and scalability - Architect data ingestion, ETL/ELT pipelines, transformation workflows, and integration patterns across internal and external data sources - Support and optimize data platforms leveraging Databricks for analytics, reporting, and advanced data engineering use cases - Design metadata management, data lineage, and catalog strategies to improve data discovery, governance, stewardship, and compliance - Collaborate with business stakeholders, system architects, data engineers, and governance teams to align data architecture with business requirements and program goals - Establish data quality frameworks, validation rules, and monitoring processes to improve data integrity and reliability - Define data security architecture including access controls, data classification, encryption, retention, and auditing requirements - Ensure compliance with CMS, federal, and healthcare data standards including HIPAA, FISMA, NIST, and interoperability requirements - Support API integrations, reporting platforms, self-service analytics, and secure data delivery through user portals and enterprise applications - Develop architecture diagrams, logical and physical data models, data dictionaries, and technical design documentation - Lead data architecture reviews and support modernization efforts for cloud migration and platform optimization Qualifications - Bachelor's degree in computer science/engineering related or equivalent degree - 8+ years of experience in Information Technology (IT) and the software development lifecycle (SDLC) - Experience with Databricks architecture, data engineering workflows, and secure analytics environments - Innovative and forward-thinking IT leader with deep knowledge of industry trends - Strong experience designing enterprise data architecture in cloud environments (AWS, Azure, or GCP) - Expertise in data modeling, data governance, metadata management, and master data management - Strong knowledge of data lake, data warehouse, and lakehouse architecture patterns - Experience with Databricks, SQL, Spark, ETL/ELT frameworks, and enterprise reporting platforms - Strong knowledge of healthcare data standards, security controls, and regulatory compliance requirements - Experience with performance optimization, data quality management, and enterprise integrations - Strong communication and stakeholder management skills Preferred Skills & Experience - Master’s degree in Computer Science/engineering related or equivalent degree - Experience building or maintaining ETL processes - Experience supporting Centers for Medicare & Medicaid Services or other federal healthcare programs - Certifications such as AWS Data Analytics, Azure Data Engineer, TOGAF, CDMP, DAMA, or cloud architecture certifications - Familiarity with Snowflake, AWS Glue, Informatica, Tableau, Power BI, Amazon QuickSight, or enterprise data governance tools - Experience working remotely using collaboration tools such as, but not limited to MS Teams, SharePoint, Slack, etc. - Skilled in managing software development life cycles using Agile/Scrum Project Management frameworks Location Leesburg, VA Work Arrangement 100% Remote Why CORMAC? At CORMAC, we leverage the power of data management and analytics to enable our customers to achieve their strategic goals. With over 20 years of experience in health information technology (HIT), human-centered design principles, and Agile development methodologies, CORMAC delivers complex digital solutions to solve some of the most challenging problems facing public healthcare programs today. As a US Federal Government contractor in the public healthcare sector, our work is impactful and cutting-edge while being performed in a supportive, collaborative, and welcoming environment. We offer flexible work schedules with remote, hybrid, or fully in-person workplace options to empower our employees to decide the workplace most suitable for them. At CORMAC, we have a highly diverse workforce and believe a work environment is a place where creativity, collaboration, enthusiasm, and innovation happen, regardless of location. US Citizenship Required /E-Verify Participation/EEO As an Equal Employment Opportunity employer, CORMAC provides equal employment opportunity to all employees and applicants without regard to an individual's protected status, including race/ethnicity, color, national origin, ancestry, religion, creed, age, gender, gender identity/expression, sexual orientation, marital status, parental status, including pregnancy, childbirth, or related conditions, disability, military service, veteran status, genetic information, or any other protected status.

**Core Responsibilities****Data Platform Architecture & Development – 40%** - Design and implement scalable data architecture across ingestion, storage, and serving layers - Build and maintain ETL/ELT pipelines integrating multiple SaaS platforms and internal systems - Develop data models supporting analytics, reporting, and AI applications - Optimize database performance, schema design, and query efficiency - Establish documentation and data standards for cross-team usability **Engineering Oversight & Standards – 25%** - Review code and architecture decisions across the engineering team - Define and enforce best practices for testing, documentation, and deployment - Identify and prioritize technical debt versus rapid delivery needs - Troubleshoot and resolve production issues across systems **AI Systems Technical Review – 20%** - Audit LLM-powered pipelines for reliability, cost efficiency, and scalability - Review prompt structures, structured outputs, and error-handling logic - Ensure clean and structured data flows into AI systems - Guide improvements in embeddings, vector storage, and evaluation datasets **Data Integration & Operations – 15%** - Manage integrations with CRMs, ATS platforms, and other SaaS tools - Handle API limitations, schema changes, and data inconsistencies - Ensure high data quality and pipeline reliability - Support cross-functional teams with data accessibility and insights

• Advanced English — will participate in daily stand-ups with international teams (USA, UK, India). • Ability to deliver results with minimal supervision • Hands-on attitude • Ability to overcome blockers independently

Role Description As a Senior Principal Data Engineer within the Enterprise Data & Analytics Office, you will lead the design, evolution, and operational excellence of Nexus, UKG’s unified, GCP-based data platform, enabling analytics, AI, and enterprise decision-making at scale. You will translate architectural vision into reliable, scalable, cost-efficient data systems, lead platform modernization efforts, and set the engineering bar for data ingestion, transformation, and operational analytics across UKG. Key Responsibilities - Enterprise Data Engineering Leadership - Drive the implementation of standardized medallion architecture (Bronze–Silver–Gold) across all domains. - Establish and enforce engineering patterns for batch, streaming, CDC, and event-driven pipelines. - Drive design patterns for Fact and Dimension modeling, data mesh, and change data capture (CDC). - Platform & Pipeline Excellence - Design and evolve scalable data pipelines using GCP-native services (BigQuery, GCS, Composer, Pub/Sub, Dataflow) and Databricks (Delta Lake, DLT). - Ensure platform reliability, performance, and scalability for petabyte-scale analytics workloads. - Lead engineering decisions around partitioning, clustering, query optimization, and cost controls (FinOps). - Own observability standards (freshness, SLAs, error handling, monitoring). - Engineering Standards, Quality & Governance - Define and enforce engineering standards for data quality, testing, CI/CD, and production readiness. - Implement automated data quality frameworks, lineage, and metadata integration in partnership with Data Governance and Architecture teams. - Ensure all pipelines meet SOX, security, and auditability requirements. - Partner with Architects to ensure engineering implementations align to enterprise reference architectures. - Cross-Functional Delivery & Influence - Partner with Product Managers, Product Owners, Architects, and Analytics leaders to deliver high-impact data capabilities. - Act as the technical escalation point for complex production issues and platform risks. - Influence roadmap decisions by balancing technical feasibility, delivery velocity, and long-term sustainability. - Support ESE Agile delivery by enabling architecture runway and reducing technical blockers. - Mentorship & Organizational Impact - Mentor Principal, Senior, and Mid-level Data Engineers, raising the overall engineering maturity of the organization. - Lead by example through design reviews, code reviews, and engineering forums. - Build reusable frameworks, libraries, and accelerators that scale engineering productivity. - Foster a culture of ownership, quality, and continuous improvement. Qualifications - 15+ years of experience in data engineering, data platforms, or large-scale analytics systems. - Proven leadership delivering enterprise-scale data platforms and migrations. - Deep hands-on experience with large (Petabyte) scale operating data platforms. Technical Expertise - GCP (required): BigQuery, GCS, Cloud Composer, Pub/Sub, Dataflow, Dataform, Dataproc, Dataplex - Databricks: Delta Lake, Delta Live Tables, Spark, Unity Catalog - Strong proficiency in Python, SQL, Spark, and distributed systems - Expertise in data modeling, ELT patterns, CDC, and streaming architectures - Experience supporting AI/ML pipelines, feature stores, and analytics consumption - Strong understanding of Dimensional Modeling, ELT and modern data lakehouse patterns. Leadership & Collaboration - Proven ability to influence without authority across engineering, product, and architecture teams. - Strong communication skills with both technical and executive audiences. - Track record of mentoring senior engineers and leading complex initiatives. Preferred Qualifications - Experience modernizing legacy warehouses and ETL platforms. - Familiarity with Data Mesh execution and domain-aligned data products. - Experience implementing FinOps practices for analytics platforms. - Exposure to AI/ML enablement, feature engineering, or agent-driven analytics. - Google Cloud certifications (Data Engineer, Architect) preferred. Benefits - The pay range for this position is $184,300 to $230,000. - The actual base pay offered may vary depending on skills, experience, job-related knowledge, and work location. - In addition to base pay, employees may be eligible to participate in a performance-based bonus plan and to receive restricted stock unit awards as part of total compensation. - Learn more about UKG’s benefits and rewards at UKG Benefits .