Business Intelligence and Analytics - Manager

EXL•Hartford, CT

3d•$90,000 - $120,000•Remote

About The Position

The Business Intelligence and 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 in the United States, with potential hires able to work from Connecticut, Texas, or Pittsburgh. The manager defines the BI roadmap in line with business priorities and KPIs; standardizes metrics and reporting; and makes decisions about dashboards, semantic models, and reports. The role oversees executive dashboards, operational reports, and self-service analytics, translating business questions into analysis, recommendations, and data stories for senior leaders. It also pilots and evaluates GenAI reporting use cases, establishes responsible-use safeguards, and trains users in AI-assisted reporting. The manager hires, coaches, and develops analysts and BI developers; manages team priorities, delivery, and quality; and builds a culture of curiosity, data literacy, and continuous improvement. As the primary point of contact for business leaders on reporting and analytics, the role partners with data engineering on models, pipelines, and quality, and enforces governance requirements for access, definitions, lineage, and compliance.

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 grasp of data warehousing concepts, including star schema, ETL/ELT, and 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 skills and ability to explain complex data to non-technical executives.
Leadership ability, including building and motivating teams, delegating, and giving clear feedback.
Business acumen, including linking metrics to revenue, cost, and customer outcomes.
Data storytelling ability to turn analysis into a clear message and recommended action.
Stakeholder management skills, including negotiating priorities and setting expectations with senior leaders.
Innovation mindset and ability to test tools such as GenAI with a clear view of value and risk.
Rigor in 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 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, aligned to business priorities and KPIs.
Standardize metrics and reporting so teams use a trusted version of the 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 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.