Business Intelligence and Analytics - Manager
EXL SERVICE
Hartford, CT, United States
16 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$90,000.0 - $120,000.0
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Data Analysis
Business Intelligence Development
BigQuery
Cloud Database
Data Validation
Information Engineering
Data Governance
Extract Transform Load (ETL)
Data Presentation
Data Warehousing
Database Queries
+19 more
Python (Programming Language)
Power BI
Cloud Services
Microsoft Copilot
Tableau (Software)
Large Language Models
Snowflake
Prompt Engineering
Generative AI
Data Layers
Microsoft Fabric
Information Technology
Data Analytics
Qlikview
Star Schema
Google Gemini
Azure Synapse Analytics
Looker Analytics
Databricks
Job description
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.
Responsibilities: 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.
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.
Preferred qualifications
- 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).
Skills and competencies
- 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.
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