Note: The job is a remote job and is open to candidates in USA. AgileOne is a workforce solutions company serving internal stakeholders and external managed service provider clients across the contingent workforce ecosystem. The Senior Data Analyst, Business Intelligence & Data Engineering leads the design and delivery of enterprise reporting, analytical datasets, semantic models, and data solutions while managing complex projects and stakeholder requirements. The role also provides technical leadership, mentorship, governance, automation, and continuous improvement for business intelligence delivery.
Responsibilities
- Lead the design, development, deployment, and maintenance of Power BI dashboards, paginated reports, analytical datasets, and executive scorecards for internal stakeholders and MSP clients
- Translate complex business requirements into clear, performant, visually intuitive reporting solutions that surface trends, exceptions, insights, and recommended actions
- Establish and enforce reporting design standards, semantic model governance, version control practices, quality assurance routines, and performance tuning expectations
- Develop reporting solutions for contingent workforce program metrics, including spend, suppliers, requisitions, bill rates, compliance, tenure, diversity, utilization, SLA performance, and program effectiveness
- Review and improve work produced by analysts to ensure accuracy, usability, stakeholder readiness, and alignment with AgileOne reporting standards
- Design and maintain advanced Power BI semantic models using dimensional modeling, star schemas, fact and dimension tables, calculated tables, role-playing dimensions, and reusable measures
- Develop complex DAX measures, calculation groups, time intelligence logic, and business rules to support scalable workforce analytics
- Write, optimize, and troubleshoot SQL queries, stored procedures, views, and data extracts across multiple source systems
- Build and support data ingestion, cleansing, transformation, reconciliation, and refresh workflows using Power Query, SQL, Microsoft Fabric pipelines, Azure data services, or comparable cloud tools
- Apply medallion architecture concepts across Bronze, Silver, and Gold analytical layers where appropriate, ensuring clean separation between raw, curated, and business-ready data assets
- Validate data lineage, integrity, and reconciliation across VMS platforms, enterprise systems, analytical layers, semantic models, and published reports
- Lead BI and data delivery projects from intake, discovery, requirements, design, build, testing, deployment, adoption, and post-implementation support
- Develop project plans, define milestones, estimate effort, assign work, manage dependencies, identify risks, escalate issues, and communicate status to leadership and business stakeholders
- Facilitate stakeholder workshops, requirements sessions, design reviews, testing cycles, and production readiness reviews
- Balance competing priorities across client, operational, leadership, and internal team demands while maintaining quality, timeline discipline, and transparent communication
- Ensure deliverables meet agreed scope, acceptance criteria, data quality expectations, security requirements, and business outcomes
- Provide day-to-day leadership, coaching, mentorship, and technical guidance to Data Analysts and other team members
- Lead peer reviews, solution design reviews, code reviews, data model reviews, and report quality checks
- Assign or coordinate work across team members, monitor progress, remove blockers, and support workload prioritization
- Build reusable templates, documentation, standards, and best practices that improve team consistency, scalability, and knowledge sharing
- Leverage Power Automate, Fabric pipelines, scheduling tools, scripting, or comparable automation capabilities to reduce manual effort and improve reliability
- Document data sources, transformations, business logic, security assumptions, refresh processes, issue resolution steps, and support procedures
- Partner with data engineering, infrastructure, security, and governance teams to align reporting solutions with enterprise standards for access, privacy, performance, and maintainability
- Stay current with Power BI, Microsoft Fabric, Azure, AWS, and analytics platform capabilities and recommend improvements that elevate AgileOne BI delivery
- Perform other job-related duties as assigned
Skills
- 7+ years of progressive experience in data analytics, business intelligence, reporting, data modeling, or related analytical roles
- 3+ years of advanced Power BI experience, including Power BI Desktop, Power BI Service, semantic models, workspace management, performance tuning, and report governance
- 3+ years of advanced SQL experience, including complex joins, aggregations, window functions, subqueries, stored procedures or views, performance optimization, and data validation
- 2+ years of practical data engineering experience involving data ingestion, transformation, orchestration, pipelines, cloud data platforms, data lakes, warehouses, lakehouses, or curated analytical layers
- Strong experience with VMS data structures and reporting concepts, including Fieldglass, Beeline, VNDLY, or comparable vendor management systems
- Demonstrated experience managing and delivering projects, including scope definition, planning, milestone management, stakeholder communication, risk mitigation, testing, deployment, and post-launch support
- Strong hands-on experience with DAX, including complex measures, calculation logic, time intelligence, reusable metrics, and performance optimization
- Strong hands-on experience with Power Query (M), data cleansing, transformation design, and refresh troubleshooting
- Solid understanding of dimensional modeling, relational databases, star schemas, fact/dimension design, semantic modeling, and analytics engineering best practices
- Experience working with large, complex datasets from multiple sources and reconciling discrepancies across systems, extracts, reporting layers, and dashboards
- Experience in contingent workforce, MSP, staffing, workforce solutions, procurement, HR, or related operational data environments
- Knowledge of workforce metrics such as spend, bill rates, markups, requisitions, placements, tenure, compliance, diversity, supplier performance, SLA performance, utilization, and program performance
- Ability to communicate complex technical and analytical concepts clearly to executive, operational, client, and technical audiences
- Leads through influence, clarity, accountability, and follow-through
- Able to manage concurrent priorities, deadlines, stakeholder expectations, and operational demands in a fast-paced environment
- Exercises independent judgment and discretion on matters of significance, including data interpretation, solution design, project priorities, risk mitigation, and stakeholder communication
- Demonstrates strong interpersonal skills, professional presence, and the ability to build trust with clients, managers, peers, and team members
- Able to coach, delegate, inspect work quality, provide constructive feedback, and help team members grow technical and business capabilities
- Able to work independently, collaborate effectively, and make informed decisions under pressure
- Ability to read, analyze, and interpret business requirements, reporting specifications, technical documentation, data models, and analytical concepts
- Ability to present information with clarity to leaders, managers, clients, customers, technical teams, and general business audiences
- Advanced Power BI Desktop and Power BI Service
- Advanced DAX, Power Query (M), and SQL
- Microsoft Fabric, Azure data services, cloud data platforms, data warehouse/lakehouse concepts, and automation tools
- Excel for analysis, reconciliation, validation, and stakeholder workbooks
- VMS systems such as Fieldglass, Beeline, VNDLY, or comparable platforms
- Collaboration and delivery tools such as Teams, SharePoint, Jira, Azure DevOps, Planner, Smartsheet, or similar tools
- Remote work environment
- Available to work overtime when required to meet project, client, production support, or business-critical deadlines
- Stand: 5 %
- Sit: 90 %
- Repetitive Motion: Telephone Use, Keyboard Activity, up to 90%
- Air and other public transportation Business Travel: Less than 5 %
- Lifting (lbs): Less than 10 lbs – less than 0% lifting
- Carrying (lbs): Less than 10 lbs
- Experience with Microsoft Fabric, including Lakehouse, Data Warehouse, Dataflows, pipelines, notebooks, semantic models, gateways, and refresh orchestration
- Working knowledge of Azure data services such as Azure Data Lake Storage, Azure SQL, Synapse Analytics, Data Factory, Key Vault, Entra ID, networking, and security fundamentals
- Exposure to AWS data environments, multi-cloud analytics strategies, or cross-platform data integration
- Experience applying Power BI security models, row-level security, object-level security, workspace governance, data sensitivity labeling, and access control practices
- Experience with advanced analytics, predictive modeling, machine learning concepts, or AI-assisted analytics use cases
- Microsoft Power BI Data Analyst Associate, Fabric Analytics Engineer, Azure Data Engineer, PMP, Agile, Scrum, or similar certifications
Benefits
- Remote work environment
Company Overview
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