Business Intelligence and Analytics - Manager

EXL•Hartford, CT

3d•Remote

About The Position

The BI & Analytics Manager owns how the business turns data into decisions. The role leads a team of analysts and BI developers, sets reporting strategy, and introduces Generative AI into modern reporting, including natural-language querying and automatically generated narrative insights. The position is remote within the United States, with potential work locations in Connecticut, Texas, or Pittsburgh. The manager defines the BI roadmap, oversees executive and operational reporting, and partners with business leaders and data engineering. The role also pilots and evaluates AI-enabled reporting tools, establishes safeguards for responsible AI use, and builds team capability in AI-assisted reporting. The posted base salary range is $90,000–$120,000 per year, plus an annual bonus. Final compensation depends on factors including skills, experience, location, and role scope; compensation may exceed the posted range in certain higher-cost zones.

Requirements

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Business, or a related field, or equivalent experience.
At least 7 years of experience in BI, analytics, or reporting, including at least 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 understanding of data warehousing concepts, including star schema, ETL/ELT, and semantic layers.
Demonstrated 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 skills and ability to explain complex data to non-technical executives.
Leadership ability to build and motivate teams, delegate effectively, and give clear feedback.
Business acumen to link metrics to revenue, cost, and customer outcomes.
Data storytelling skills to turn analysis into clear messages and recommended actions.
Stakeholder management skills, including negotiating priorities and setting expectations with senior leaders.
Innovation mindset and ability to test tools such as GenAI while considering value and risk.
Rigor in maintaining data quality, reconciliation, and documented definitions.

Nice To Haves

Master's degree or MBA.
Experience with AI features in BI tools, such as Copilot in Power BI, Tableau AI, or 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 skills for analysis and automation.
Knowledge of data governance, privacy, and responsible-AI practices.
Relevant certifications, such as Microsoft PL-300, Tableau Certified, or a cloud data certification.

Responsibilities

Define and own the BI roadmap, aligning it with business priorities and KPIs.
Standardize metrics and reporting so teams use a trusted version of business numbers.
Decide what to build, buy, or retire across dashboards, semantic models, and reports.
Oversee the 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.
Identify and pilot GenAI reporting use cases, including 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 effective solutions.
Set responsible-AI guardrails, including data privacy, accuracy checks, and human review of AI-generated insights.
Train analysts and business users to use AI-assisted reporting effectively.
Hire, coach, and develop analysts and BI developers; set goals and conduct 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.
Serve as the main point of contact for business leaders on reporting and analytics needs.
Work with data engineering on data models, pipelines, and data quality.
Enforce data governance requirements, including access controls, definitions, lineage, and compliance.