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BI Lab Project Lead

Ecolab
Pune, IND
Full-time
Senior · 10+ years experience
Onsite
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What’s in it For You

You will join a growth company offering a competitive salary and benefits.

The ability to make an impact and shape your career with a company that is passionate about growth.

The support of an organization that believes it is vital to include and engage diverse people, perspectives and ideas to achieve our best.

Feel proud each day to work for a company that provides clean water, safe food, abundant energy and healthy environments.

Role Summary

The Analytics Lead is a business-outcomes focused leader who sits at the intersection of business, analytics, and data science. This role is responsible for translating ambiguous business questions from business stakeholders into clear, actionable analytical projects. Those projects will allow your team to deliver insights that drive different and more profitable decisions across Ecolab.

This individual will work iteratively with a variety of stakeholders across the enterprise. The day-to-day may include rapidly prototyping, refining solutions 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.

Success in this role is defined not by technical complexity, but by the ability to deliver relevant, impactful, and scalable 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
  • 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. Iterate based on feedback to refine solutions.
  • Move quickly from problem definition to gathering data to delivering an insight.
  • Deliver early versions of analyses, dashboards, models, or lightweight tools.
  • Iterate based on feedback to refine solutions.
  • Apply the appropriate analytical approach Work with stakeholders to 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).
  • Work with stakeholders to 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 Databricks or Python to create a scaled and tested data model for consumption.
  • Use SQL or Python to source, clean, and transform data into useable data for analysis. If engaged in scaling data transformation, leverage Databricks or Python 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 and relevant to business needs.
  • 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 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
  • Translate prototypes into clear requirements for BI developers and data engineers
  • Partner cross-functionally to scale solutions into production
  • Operate flexibly between guiding team and execution Provide direction and oversight when resources allow Contribute hands-on development when needed in resource-constrained environments
  • 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
  • Use outputs to guide and advance stakeholder conversations
  • Continuously refine questions and approaches through iteration

Required Qualifications

  • 10+ years of experience in analytics, business intelligence, or data science
  • Experience working directly with stakeholders and iterating on analytical outputs
  • Demonstrated ability to translate business problems into analytical approaches and solutions
  • Strong problem-framing and prioritization skills, with a focus on business impact
  • Strong proficiency in SQL and Python

Preferred Qualifications

  • Experience with Databricks or Python for data transformation and modeling
  • Experience building lightweight applications or prototypes using Python.
  • 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 using Claude Code or similar GenAI development tools.

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