Lead business intelligence reporting initiatives by gathering requirements, defining dashboard scope, mapping data sources, creating wireframes and specifications, and coordinating data engineering teams. Facilitate workshops, manage reporting backlogs, conduct functional testing and reconciliation, coordinate UAT and defect resolution, and oversee deployment and post-production validation. The role also contributes to data engineering strategy, innovation, executive presentations, and long-term data planning.
Key Responsibilities
- Conduct workshops with business users, product owners, data owners, and technology stakeholders.
- Understand business objectives, reporting use cases, user personas, KPIs, and analytical requirements.
- Define the scope and priority of each new QuickSight report or dashboard.
- Prepare report wireframes or mock-ups and obtain client approval.
- Identify source tables, views, fields, joins, filters, and data granularity.
- Document source-to-report mappings and transformation rules
- Coordinate with the client’s data-engineering team in lieu of Reporting Data requirements
- Maintain the reporting backlog, priorities & RAID
- Perform functional testing and data reconciliation.
- Coordinate report demonstrations, UAT, defect resolution, and business sign-off.
- Coordinate report demonstrations, UAT, defect resolution, and business sign-off.
- Coordinate production deployment and post-production validation.
Required Skills and Experience:
- Approximately 8–12 years of experience in business intelligence, reporting, business analysis, or data analytics.
- Strong experience gathering and documenting dashboard and reporting requirements.
- Strong SQL and data-analysis skills.
- Working knowledge of Amazon QuickSight datasets, analyses, dashboards, calculated fields, parameters, filters, SPICE, direct query, and security.
- Strong understanding of KPIs, dimensional data models, aggregations, data granularity, and reconciliation.
- Experience preparing report specifications, source-to-report mappings, wireframes, and acceptance criteria.
- Strong client-facing, workshop-facilitation, documentation, and communication skills.
Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.
Base Compensation Range: $110,000- $130,000
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
About Us EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
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