BI Lab Manager

BI Lab Manager

Job Description

Ecolab seeks a business-centric analytics professional who excels at turning ambiguous questions into actionable insights and has deep expertise in evolving those insights into scalable, production-ready solutions.

This role is the leader of a small team that sits at the intersection of business strategy, data, and product thinking. The primary strength of this role is the ability to quickly understand business context, translate it into meaningful metrics and analyses, and deliver relevant outputs that move decision-making forward.

In addition to leading the team, this individual will work iteratively with a variety of stakeholders across the enterprise. The day-to-day may include rapidly prototyping analyses, tools, or visualizations, refining them with stakeholders, and ultimately identifying which solutions should be scaled. As solutions mature, they will partner with BI developers and data engineers to operationalize them.

The person in this role will either facilitate the start of scaled solutions or they may contribute to hands-on delivery of scaled solution.

Success in this role is defined not by technical complexity, but by the ability to deliver relevant, impactful, data solutions.

Key Responsibilities:

• Translate business needs into data-driven solutions
  • Engage stakeholders to understand goals, context, and constraints
  • Identify the most relevant questions, metrics, and drivers of value
• Rapidly prototype insights and analytical tools
  • Move quickly from problem definition to gathering data to delivering an insight.
  • Deliver early versions of analyses, dashboards, models, or lightweight tools either via PowerPoint, PowerBI, Streamlit, or custom AI tools.
  • Iterate based on feedback to refine usefulness and clarity

• Apply the appropriate analytical approach
  • Determine when to use visualization, statistical analysis, modeling, or simple heuristics to a business problem.
  • Balance speed, rigor, and usability based on the situation (including the maturity of the question and the needs of the business).
• Perform data transformation and analysis
  • Use SQL or Python to source, clean, and transform data into useable data for analysis. If engaged in scaling data transformation, leverage dbt to create a scaled and tested data model for consumption.
• Design meaningful metrics and outputs
  • Define metrics that align with real business outcomes. Work with stakeholders to understand gaps in metric definitions or propose functional alternatives.
  • Ensure outputs are interpretable, actionable, and relevant to business needs.
• Evolve prototypes into scalable solutions
  • Translate prototypes into clear requirements for BI developers and data engineers
  • Partner cross-functionally to scale solutions into production
  • Sometimes contribute to scaled products.
• Operate flexibly between guidance and execution
  • Provide direction and oversight when resources allow
  • Contribute hands-on development when needed in resource-constrained environments
• Drive insight-led decision-making
  • Use outputs to guide and advance stakeholder conversations
  • Continuously refine questions and approaches through iteration
• Team Leadership
  • Coach direct reports and “dotted line” analysts on ways to improve solution development.

Required Qualifications:

• 12+ years of experience in analytics, business intelligence, or data science
• 3-5 Years of Direct People Management Experience
• Strong proficiency in SQL for data extraction and transformation
• Proficiency in Python for data manipulation, analysis, or prototyping
• Experience with data visualization tools (e.g., Power BI, Tableau, Looker, or similar)
• Demonstrated ability to translate business problems into analytical approaches and solutions
• Experience working directly with stakeholders and iterating on analytical outputs
• Strong problem-framing and prioritization skills, with a focus on business impact

Preferred Qualifications:

• Experience with dbt for data transformation and modeling
• Experience building lightweight applications or prototypes using tools such as Streamlit.
• Familiarity with semantic models in Snowflake
• Experience with AI-enabled analytics tools such as Snowflake Cortex Agent or Databricks Genie.
• Experience implementing or supporting data quality testing frameworks.
• Exposure to product-oriented thinking in analytics (e.g., scaling dashboards, tools, or data products)
• Ability to translate exploratory work into structured requirements for engineering teams
• Experience with GitHub or other CI/CD pipeline tools.
• Experience using Claude Code or similar GenAI development tools.

Experience Level

Senior Level