Business Intelligence and Analytics - Manager
$90 K-$120 K /Yr
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Posted 11 days ago
SENIORITY
Manager
SALARY
$90 K-$120 K /Yr
About the role
- 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.
- 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.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
