TECHNOGEN, Inc. is a Proven Leader in providing full IT Services, Software Development and Solutions for 15 years.
TECHNOGEN is a Small & Woman Owned Minority Business with GSA Advantage Certification. We have offices in VA; MD & Offshore development centers in India. We have successfully executed 100+ projects for clients ranging from small business and non-profits to Fortune 50 companies and federal, state and local agencies.
Job Title: Senior Data Solutions Analyst Enterprise Data
Location: Remote / Home-Based, US Based
Position Summary
We are seeking a Senior Data Solutions Analyst - Enterprise Data to lead the functional design and governance of reusable enterprise data products. Serving as the bridge between business stakeholders and our Azure Data Engineering and Business Intelligence teams, this role combines business consulting, enterprise metric design, advanced SQL development, semantic model requirements, master data governance, and functional solution design. The successful candidate will work directly with Finance, Operations, Sales, HR, Product, and Technology teams to define and certify enterprise metrics, shape governed Gold Layer data products and Power BI semantic models, establish business rules for enterprise master data, and prepare trusted data for reporting, APIs, analytics, and AI-enabled use cases.
Responsibilities
- Partner with business leaders to understand processes, pain points, reporting needs, enterprise KPI requirements, and opportunities for governed data and AI-enabled solutions.
- Facilitate requirements and definition workshops, resolve conflicting interpretations, and translate business objectives into functional requirements, business rules, acceptance criteria, and technical specifications.
- Lead the definition, certification, and ongoing governance of enterprise metrics, including calculations, dimensions, time periods, inclusions, exclusions, ownership, and change impacts.
- Develop complex SQL queries to profile data, prototype and validate business logic, and reconcile results across multiple source systems.
- Lead the functional design of reusable Gold Layer data products and partner with Azure Data Engineers to implement appropriate Bronze ingestion, Silver conformance, and governed Gold outputs.
- Define business and analytical requirements for enterprise Power BI semantic models, including facts, dimensions, measures, hierarchies, relationships, usability, and business-facing row-level security requirements.
- Partner with Business Intelligence teams to ensure semantic model measures and report outputs remain consistent with certified Gold Layer definitions and to rationalize duplicated or inconsistent report-level logic.
- Lead business discovery and functional design for enterprise master data domains, including data ownership, authoritative sources, matching and standardization rules, survivorship, hierarchies, crosswalks, and exception handling.
- Coordinate with business data owners and stewards to establish data-quality standards, resolve master data issues, and maintain trusted enterprise definitions.
- Define reusable, well-documented data products and semantic context that enable responsible use of Power BI, APIs, Databricks Genie, copilots, and other AI or analytics capabilities.
- Evaluate proposed AI use cases for data readiness, appropriate governed sources, business definitions, limitations, and validation requirements; partner with Engineering, Security, and application teams on implementation.
- Lead UAT, reconciliation, business-owner review, and certification, ensuring solutions meet functional requirements before production release.
- Maintain the business glossary, metadata, KPI catalog, lineage, ownership, certification status, and business-to-technical mappings for enterprise data products.
- Assess downstream impacts of changes to source data, master data, Gold Layer structures, KPIs, and semantic models, and coordinate required validation and stakeholder communication.
- Identify opportunities to standardize, automate, and improve enterprise reporting, analytics, master data, and governed self-service consumption.
Qualifications
- Bachelor's degree in Computer Science, Information Systems, Business Analytics, Engineering, Finance, or a related field.
- 13+ years of experience in Data Analytics, Business Intelligence, Data Solutions, Data Product, Master Data, or Analytics Consulting roles.
- Advanced SQL skills, including CTEs, window functions, aggregations, complex joins, and query optimization.
- Strong understanding of dimensional modeling, fact and dimension design, enterprise data warehousing, and Medallion architecture.
- Experience translating ambiguous business needs into production-ready functional requirements, governed business rules, and acceptance criteria.
- Experience defining or supporting reusable Power BI semantic models, including measures, relationships, hierarchies, and row-level security concepts.
- Experience with master data management or data governance concepts, including ownership, stewardship, matching, survivorship, hierarchy management, and data-quality rules.
- Working knowledge of Azure Data Lake, Databricks, Azure Data Factory, Unity Catalog, or similar cloud data platforms.
- Understanding of how governed enterprise data, metadata, and semantic context support AI assistants, natural-language analytics, and other AI-enabled applications.
- Excellent communication and facilitation skills, with the ability to work comfortably with executives, business owners, analysts, and technical teams.
- Strong analytical, problem-solving, documentation, and cross-functional leadership skills.
- Success Measures
- Certified enterprise metrics and governed data products delivered accurately and on schedule.
- Consistent definitions and results across Gold Layer assets, Power BI semantic models, reports, APIs, and approved AI-enabled use cases.
- Master data domains supported by clear ownership, approved business rules, measurable data quality, and effective exception resolution.
- High-quality SQL prototypes and functional specifications that minimize engineering rework.
- Effective UAT, certification, change-impact management, and partnership between business stakeholders, Business Intelligence, and Engineering.
- Increased adoption and trusted use of governed enterprise data products.
Govinda rajulu. M| Sr. Talent Acquisition Specialist
