Senior Data Solutions Analyst – Enterprise Data

Job not on LinkedIn

🔥 1 hour ago

🇺🇸 United States – Remote

💵 $72 - $80 / hour

⏳ Contract/Temporary

🟠 Senior

🧐 Business Analyst

👻 Ghost score 22%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 37 days.
• 45 open roles for a team of 21.

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aKUBE

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

aKUBE is a recruitment firm that specializes in connecting top-tier IT professionals with innovative companies. They emphasize a quality-focused approach to recruiting, ensuring a perfect match between candidates and company values. By leveraging advanced technology and a refined process, aKUBE streamlines staffing solutions that align with client timelines while offering services like contract staffing, direct hire placements, and payroll management. Their commitment to performance and client partnerships positions aKUBE as a trusted partner in achieving business success through tailored staffing solutions.

📋 Description

• 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

🎯 Requirements

• 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 • 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 • Experience with Azure Data Lake, Azure Data Factory, Databricks, or Unity Catalog is nice to have • Experience supporting AI-enabled analytics, natural-language querying, copilots, or Databricks Genie is nice to have • Experience defining enterprise data products used by APIs and AI applications is nice to have • Experience managing enterprise KPI catalogs, metadata repositories, and data lineage is nice to have

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