Note: The job is a remote job and is open to candidates in USA. Access | Information Management is seeking a Senior Data Analyst to build trusted Finance data products and expand self-service analytics across FP&A. The role will develop data models, transformations, pipelines, semantic models, dashboards, and advanced analytical solutions while partnering with Finance and Shared Data Services teams to validate, operationalize, and govern data assets.
Responsibilities
- Build, enhance, and maintain Finance tables, views, transformations, pipelines, and analytical models within established enterprise architecture, security, development, and governance standards
- Develop reusable data products supporting bookings, customers, billing, revenue, operational activity, and portfolio performance
- Use SQL and Python to automate data preparation, validation, and analytical workflows, and convert repeatable analyses into scalable assets
- Apply appropriate source control, testing, deployment, monitoring, and documentation practices to Finance data products
- Translate FP&A and Portfolio Analytics needs into clear source requirements, data grain, business rules, transformation logic, quality controls, and acceptance criteria
- Own Finance requirements, prioritization, validation, and acceptance for data products delivered in partnership with onshore and offshore Shared Data Services teams
- Reconcile outputs to source systems, financial reporting, operational reporting, and approved methodologies; identify and resolve data quality issues, logic gaps, hierarchy problems, and incomplete coverage
- Maintain documentation for metric definitions, data lineage, business rules, assumptions, and known limitations, and coordinate issue resolution through Finance sign-off
- Use SQL, Python, and appropriate analytical methods to solve complex customer, revenue, pricing, forecasting, portfolio, and operational questions
- Build semantic models, dashboards, and analytical tools using Power BI or a comparable enterprise business intelligence platform
- Enable FP&A users to independently answer recurring business questions with trusted data, reducing manual extracts, spreadsheet-based preparation, and one-off reporting
- Use approved AI-assisted development tools to improve coding, testing, documentation, and analytical productivity while validating outputs and protecting confidential data
Skills
- • Bachelor's degree in a technical, quantitative, analytical, Finance, or business discipline; equivalent relevant professional experience may be considered
- • Five or more years of relevant experience in data analytics, analytics engineering, data engineering, business intelligence, or a related field
- • Demonstrated experience independently delivering complex data and analytical solutions. Finance, FP&A, commercial analytics, or executive reporting experience is helpful but not required
- • Advanced SQL and strong dimensional and analytical data-modeling skills
- • Proficiency in Python for data processing, automation, and advanced analytics
- • Experience developing or supporting ETL/ELT pipelines and reusable analytical datasets
- • Hands-on experience with a modern cloud data warehouse or lakehouse environment
- • Experience with data reconciliation, quality assurance, troubleshooting, and documentation
- • Experience developing semantic models, dashboards, or business intelligence solutions
- • Ability to translate ambiguous business requirements into scalable analytical and technical solutions
- • Familiarity with source control, testing, deployment, and production support practices
- • Strong technical problem-solving skills and the ability to execute independently
- • Consultative approach and the ability to communicate effectively with technical and nontechnical stakeholders
- • Strong attention to data accuracy, controls, validation, and methodological consistency
- • Ability to manage multiple priorities, dependencies, and deliverables with clear follow-through
- • Curiosity, sound judgment, and a bias toward action and iterative delivery
- • Ability to learn new technologies, data sources, and business concepts quickly
- • Experience with Microsoft Fabric and Azure data services, including lakehouses, warehouses, notebooks, pipelines, or related analytical workloads
- • Power BI experience, including semantic modeling and DAX
- • Experience with Git, CI/CD, orchestration, monitoring, or production support
- • Experience supporting Finance, FP&A, commercial analytics, or executive reporting
- • Familiarity with forecasting, customer analytics, revenue analytics, or portfolio analytics
- • Experience working with centralized or shared enterprise data teams
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