Senior Data Solutions Analyst – Enterprise Data - 1670

Akube; United States; À distance; USD 99 000 - 110 000; Plein temps

Résumé du poste

Akube is seeking a Senior Data Solutions Analyst for Enterprise Data. The role focuses on governance of enterprise data products, KPI definitions, and advanced SQL within cloud platforms like Azure/Databricks.

You will collaborate with Finance, Operations, Sales, HR, Product, and Technology to define reporting needs and ensure data quality. The candidate will translate business requirements into functional specs, lead data workshops, and certify data KPIs.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Business Analytics, Engineering, Finance, or a related field.
• Minimum 5 years of experience in Data Analytics, Business Intelligence, Data Solutions, Data Product, Master Data, or Analytics Consulting.
• Strong experience writing and optimizing complex SQL queries.
• Understanding of dimensional modeling, enterprise data warehousing, and Medallion architecture.
• Experience defining production-ready functional requirements and governed business rules.
• Experience with Power BI semantic models and enterprise reporting.
• Knowledge of master data governance, stewardship, data quality, and business definitions.
• Experience leading business requirements workshops, UAT, and data validation.
• Ability to coordinate with business stakeholders, data engineers, and BI teams.

Responsabilités

• Lead functional design and governance of reusable enterprise data products.
• Partner with Finance, Operations, Sales, HR, Product, and Technology teams to define enterprise reporting and analytics requirements.
• Conduct business workshops and translate requirements into functional specifications, business rules, and acceptance criteria.
• Define, document, and certify enterprise KPIs, including calculations, dimensions, ownership, and change impacts.
• Develop advanced SQL queries for data profiling, validation, reconciliation, and business logic testing.
• Design governed Gold Layer data products and collaborate with Data Engineering teams on Bronze, Silver, and Gold architectures.
• Define requirements for Power BI semantic models, including measures, relationships, hierarchies, and security.
• Establish master data rules covering matching, standardization, survivorship, hierarchies, and exception handling.
• Work with data owners and stewards to improve data quality and maintain consistent enterprise definitions.
• Support governed data consumption through APIs, Power BI, Databricks Genie, and AI-enabled applications.
• Evaluate AI use cases for data readiness, governance, business definitions, and validation requirements.
• Lead user acceptance testing (UAT), reconciliation, business validation, and data product certification.
• Maintain data dictionaries, business glossaries, KPI catalogs, metadata, lineage, and ownership documentation.
• Assess downstream impacts of changes to data sources, enterprise metrics, and semantic models.

Connaissances

Advanced SQL

Dimensional modeling

Data warehousing

KPIs & governance

Power BI modeling

MDM / governance

Requirements gathering

Azure / Databricks

APIs & data consumption

UAT / data validation

Formation

Bachelor's degree in CS/IS/Analytics/Engineering/Finance

Outils

Azure Data Lake

Azure Data Factory

Databricks

Unity Catalog

Description du poste

Senior Data Solutions Analyst – Enterprise Data - 1670

Onsite/ Hybrid/ Remote: Remote (EST only)

Duration: 6 months contract to hire

Rate Range: Up to $80/hr on C2C or $72/hr on W2
Work Authorization: GC, USC Only

Must Have:

Advanced SQL, including CTEs, window functions, complex joins, aggregations, and query optimization.

Enterprise data warehousing and dimensional modeling, including fact and dimension design.

Experience defining enterprise KPIs, business rules, and governed data products.

Power BI semantic modeling, including measures, relationships, hierarchies, and row-level security concepts.

Master Data Management (MDM) or enterprise data governance experience.

Experience translating business requirements into functional specifications and acceptance criteria.

Working knowledge of Azure, Databricks, or similar cloud data platforms.

Responsibilities:

Lead functional design and governance of reusable enterprise data products.

Partner with Finance, Operations, Sales, HR, Product, and Technology teams to define enterprise reporting and analytics requirements.

Conduct business workshops and translate requirements into functional specifications, business rules, and acceptance criteria.

Define, document, and certify enterprise KPIs, including calculations, dimensions, ownership, and change impacts.

Develop advanced SQL queries for data profiling, validation, reconciliation, and business logic testing.

Design governed Gold Layer data products and collaborate with Data Engineering teams on Bronze, Silver, and Gold architectures.

Define requirements for Power BI semantic models, including measures, relationships, hierarchies, and security.

Establish master data rules covering matching, standardization, survivorship, hierarchies, and exception handling.

Work with data owners and stewards to improve data quality and maintain consistent enterprise definitions.

Support governed data consumption through APIs, Power BI, Databricks Genie, and AI-enabled applications.

Evaluate AI use cases for data readiness, governance, business definitions, and validation requirements.

Lead user acceptance testing (UAT), reconciliation, business validation, and data product certification.

Maintain data dictionaries, business glossaries, KPI catalogs, metadata, lineage, and ownership documentation.

Assess downstream impacts of changes to data sources, enterprise metrics, and semantic models.

Qualifications:

Bachelor's degree in Computer Science, Information Systems, Business Analytics, Engineering, Finance, or a related field.

Minimum 5 years of experience in Data Analytics, Business Intelligence, Data Solutions, Data Product, Master Data, or Analytics Consulting.

Strong experience writing and optimizing complex SQL queries.

Understanding of dimensional modeling, enterprise data warehousing, and Medallion architecture.

Experience defining production-ready functional requirements and governed business rules.

Experience with Power BI semantic models and enterprise reporting.

Knowledge of master data governance, stewardship, data quality, and business definitions.

Experience leading business requirements workshops, UAT, and data validation.

Ability to coordinate with business stakeholders, data engineers, and BI teams.

Nice to Have:

Experience with Azure Data Lake, Azure Data Factory, Databricks, or Unity Catalog.

Experience supporting AI-enabled analytics, natural-language querying, copilots, or Databricks Genie.

Experience defining enterprise data products used by APIs and AI applications.

Experience managing enterprise KPI catalogs, metadata repositories, and data lineage.