TTEC Digital
Website:
ttecdigital.com
Job details:
At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive.
Job Description
Microsoft Fabric Analytics BA and Developer
Overview
TTEC Digital is seeking a Microsoft Fabric Analytics BA and Developer to help design, build, and support enterprise analytics solutions across Microsoft Fabric, Power BI, OneLake, lakehouses, warehouses, semantic models, data pipelines, and reporting experiences. This hybrid role bridges business analysis and hands-on development: partnering with stakeholders to define reporting needs, translate requirements into analytics-ready designs, and deliver governed, scalable data products that improve decision-making across the organization. The ideal candidate is comfortable moving between business conversations, data modeling, report development, testing, documentation, and production support within an Agile delivery model.
Responsibilities
- Business Analysis and Requirements Definition
- Partner with business stakeholders, product owners, analysts, and technical teams to understand reporting needs, business processes, data definitions, and decision-making objectives
- Translate business requests into clear requirements, user stories, acceptance criteria, process flows, data mappings, and report specifications
- Facilitate discovery sessions to clarify source systems, metric definitions, calculation logic, security needs, refresh expectations, and user experience requirements
- Identify gaps, dependencies, risks, and data quality concerns early, and recommend practical options that balance speed, scalability, governance, and business value
- Maintain functional documentation that supports development, testing, adoption, training, and long-term support
- Microsoft Fabric Solution Development
- Design, develop, test, and support analytics assets in Microsoft Fabric, including lake houses, warehouses, dataflows, pipelines, semantic models, and Power BI reports
- Build and maintain data ingestion, transformation, and orchestration patterns using Fabric Data Factory, Dataflows Gen2, notebooks, SQL, or other approved Fabric capabilities
- Create curated, analytics-ready data structures using OneLake, lakehouse, warehouse, and dimensional modeling patterns
- Develop reusable semantic models that support consistent measures, relationships, hierarchies, security, performance, and enterprise reporting standards
- Apply Microsoft Fabric best practices for workspace organization, item ownership, deployment readiness, monitoring, and supportability
- Power BI Reporting, Analytics, and Data Modeling
- Design, build, and enhance Power BI reports, dashboards, and analytical experiences that are intuitive, performant, and aligned to stakeholder needs
- Develop semantic models, DAX measures, relationships, calculation logic, and report interactions that support accurate and reusable analytics
- Optimize report performance, model design, refresh patterns, and user experience across enterprise-scale datasets
- Support data validation, reconciliation, and metric governance to ensure business users trust the outputs they consume
- Collaborate with business users to interpret findings, refine reporting requirements, and improve adoption of analytics solutions
- Data Governance, Security, and Lifecycle Management
- Follow enterprise standards for data access, workspace security, sensitivity, privacy, retention, compliance, and operational support
- Implement and validate appropriate security patterns, including workspace permissions, item access, row-level security, object-level security, and data-sharing controls where applicable
- Use approved lifecycle practices such as Git integration, deployment pipelines, Azure DevOps, version control, release documentation, and deployment validation
- Document data lineage, source-to-target mappings, transformation logic, model assumptions, refresh dependencies, and support procedures
- Partner with administrators, architects, and data owners to align Fabric solutions with governance, capacity, monitoring, and platform standards
- Agile Delivery, Testing, and Stakeholder Enablement
- Participate actively in sprint planning, backlog refinement, demos, retrospectives, solution design discussions, and release readiness activities
- Lead or support unit testing, data validation, system testing, user acceptance testing, defect triage, and production of hyper care
- Create clear release notes, training materials, support documentation, and adoption guidance for analytics consumers
- Communicate progress, risks, dependencies, data limitations, and technical tradeoffs clearly to both technical and non-technical stakeholders
- Provide knowledge sharing and enablement to business users, analysts, report developers, and support teams to improve analytics maturity and self-service adoption
Qualifications
Required Skills and Experience
- Bachelor's degree in information systems, Computer Science, Data Analytics, Business, or a related field; or equivalent professional experience
- 4+ years of experience in business intelligence, analytics, data analysis, data engineering, reporting, or related technology delivery
- Hands-on experience with Microsoft Fabric, Power BI, or related Microsoft analytics technologies
- Strong business analysis skills, including requirements gathering, user story creation, acceptance criteria, data mapping, process analysis, and stakeholder facilitation
- Experience building Power BI reports, dashboards, semantic models, DAX measures, and reusable reporting datasets
- Working knowledge of SQL, dimensional modeling, data quality validation, source-to-target mapping, and analytical data design
- Familiarity with Microsoft Fabric concepts such as OneLake, lakehouses, warehouses, data pipelines, dataflows, notebooks, deployment pipelines, and workspace management
- Ability to troubleshoot reporting, model, refresh, data quality, permissions, and production support issues across development, test, and production environments
- Excellent written and verbal communication skills, including the ability to explain data concepts and technical tradeoffs clearly to non-technical stakeholders
Preferred Skills
- Microsoft Fabric Analytics Engineer Associate, Power BI Data Analyst Associate, Fabric Data Engineer Associate, or related Microsoft certification
- Experience with Microsoft Fabric lakehouse or warehouse architecture, Medallion patterns, Direct Lake, shortcuts, mirroring, or enterprise-scale semantic model design
- Experience with PySpark, KQL, T-SQL, Dataflows Gen2, Fabric notebooks, Real-Time Intelligence, or advanced data pipeline development
- Experience with Git integration, Azure DevOps, deployment pipelines, release management, and governed analytics lifecycle practices
- Familiarity with Microsoft Purview, data cataloging, lineage, sensitivity labels, data governance, and enterprise security practices
- Experience working in a Microsoft partner, consulting, professional services, CX, contact center, or enterprise IT environment
Key Attributes
- Business-outcome mindset: connects analytics capability to better decisions, operational visibility, productivity, and measurable business value
- Analytical curiosity: asks strong questions, validates assumptions, and digs into data issues until the business meaning is clear
- Systems thinking understands how source systems, pipelines, data models, security, reports, governance, and adoption work together across an analytics platform
- Delivery discipline: moves quickly while maintaining quality, documentation, testing, traceability, and supportability
- Governance-minded: designs with access, data protection, metric consistency, lineage, and long-term ownership in mind from the start
- Collaborative: builds productive relationships with business stakeholders, data owners, analysts, architects, administrators, developers, and support teams
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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