Business Intelligence and Analytics - Manager

Work Location: United States

Work Mode : Remote / Potential hire can work from Connecticut / Texas or from Pittsburgh

Pay Range :$90K-$120K /Yr Base + Annual Bonus

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

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

Job Overview:

We are hiring a BI & Analytics Manager to own how the business turns data into decisions. You will lead a team of analysts and BI developers, set the reporting strategy, and bring Generative AI into modern reporting, from natural-language querying to auto-generated narrative insights.

BI and reporting strategy

• Define and own the BI roadmap, aligned to business priorities and KPIs.
• Standardize metrics and reporting so every team works from one trusted version of the numbers.
• Decide what to build, buy or retire across dashboards, semantic models and reports.

Analytics and report delivery

• Oversee design and delivery of executive dashboards, operational reports and self-service analytics.
• Translate business questions into clear analysis, recommendations and data stories for senior leaders.
• Ensure reports are accurate, timely, documented and easy to use.

GenAI-enabled modern reporting

• Identify and pilot GenAI use cases in reporting: natural-language queries, automated commentary, anomaly explanations and report summarization.
• Evaluate AI features in BI platforms and LLM-based tools; run proofs of concept and scale what works.
• Set guardrails for responsible AI use, including data privacy, accuracy checks and human review of AI-generated insights.
• Train analysts and business users to use AI-assisted reporting effectively.

Team leadership

• Hire, coach and develop analysts and BI developers; set goals and run performance reviews.
• Prioritize the team's backlog and manage delivery against deadlines and quality standards.
• Build a culture of curiosity, data literacy and continuous improvement.

Stakeholder partnership and governance

• Act as the main point of contact for business leaders on reporting and analytics needs.
• Work with data engineering on data models, pipelines and quality.
• Enforce data governance: access controls, definitions, lineage and compliance requirements.

• Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Business or a related field (or equivalent experience).
• 7+ years in BI, analytics or reporting, including 2+ years leading or managing a team.
• Hands-on expertise with at least one major BI platform (Power BI, Tableau, Looker or Qlik), including data modeling and dashboard design.
• Strong SQL skills and a solid grasp of data warehousing concepts (star schema, ETL/ELT, semantic layers).
• Proven record of designing and delivering executive-level reports and analytics that drove business decisions.
• Working knowledge of how GenAI and LLMs apply to reporting and analytics, with practical exposure through a pilot, project or tool adoption.
• Excellent communication: able to explain complex data to non-technical executives.

• Master's degree or MBA.
• Experience with AI features in BI tools (for example Copilot in Power BI, Tableau AI, Gemini in Looker) or with LLM APIs for reporting use cases.
• Familiarity with prompt design, retrieval-augmented generation (RAG) and evaluating AI output quality.
• Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, Azure Synapse or Microsoft Fabric.
• Python or R for analysis and automation.
• Knowledge of data governance, privacy and responsible-AI practices.
• Relevant certifications (for example Microsoft PL-300, Tableau Certified, or a cloud data certification).

• Leadership: builds and motivates teams, delegates well, gives clear feedback.
• Business acumen: links metrics to revenue, cost and customer outcomes.
• Data storytelling: turns analysis into a clear message and a recommended action.
• Stakeholder management: negotiates priorities and sets expectations with senior leaders.
• Innovation mindset: tests new tools such as GenAI with a clear view of value and risk.
• Rigor: insists on data quality, reconciliation and documented definitions.