Data Analyst

Overview

Claro Energy is a leading clean energy company in India with 15+ years of experience in building decentralized renewable energy solutions. We have delivered 1,00,000+ solar projects across solar irrigation pumps, rooftop solar, and large-scale clean energy programs, working closely with farmers, households, institutions, and government initiatives across multiple Indian states.

As we scale further, we are building an AI-first data and intelligence foundation to power automation, forecasting, and faster decision-making across operations, growth, inventory, and finance.

We are hiring an AI-First Data Engineer / Data Operations Engineer to help us turn large volumes of real-world operational data into AI-ready systems .

This is not a traditional reporting or dashboard-only role

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The focus is on preparing, structuring, and operationalising data so it can directly power:

• AI workflows
• Automation systems
• Forecasting and prioritisation logic
• Decision support tools

You will work closely with AI engineers, automation systems, CRM, and operations teams to ensure Claro’s data is clean, connected, and usable by machines — not just humans .

• Design and maintain AI-ready data models for consumer, lead, ops, and installation data
• Clean, structure, and continuously improve large, messy real-world datasets
• Build and maintain data pipelines that feed AI workflows, automation systems and internal tools and agents
• Ensure data consistency across CRM systems, Databases, Automation workflows and Internal applications
• Prepare datasets that support Classification, Prioritisation, Forecasting, and Recommendation logic
• Create reliable data views and reports used by AI systems, Operations teams, and Leadership
• Work with AI engineers to define features, aggregations, and signals needed for future ML/AI systems
• Improve data validation, hygiene, and documentation over time

You should be comfortable working on data problems involving:

• AI-first data preparation (data built for automation and models, not just reports)
• Operational data at scale (leads, installations, timelines, vendors, geography)
• Database design that supports evolving AI and automation needs
• Data reconciliation across multiple tools and systems
• Structured outputs that can be consumed by AI agents and workflows

Strong interest or exposure to any of the following is a plus:

• Preparing datasets for machine learning or predictive systems
• Supporting forecasting (demand, timelines, region-wise trends)
• Feature engineering for lead quality scoring, delay or risk prediction and inventory or vendor optimisation
• Working with semi-structured data from APIs and automation tools
• Enabling AI-assisted systems for Operations planning, Inventory tracking and Finance or risk signals

To succeed in this role, you should have:

• 1–3 years of experience in data engineering, data operations, or analytics with engineering depth and AI-first approach
• Strong hands-on experience with SQL (mandatory)
• Advanced proficiency in Excel / Google Sheets (pivots, formulas, data cleaning, etc.).
• Familiarity with visualization tools like Tableau, Power BI, or Looker Studio — nice to have but not mandatory.
• Experience designing and working with relational databases (PostgreSQL / MySQL or similar)
• Working knowledge of Python, Google Apps Script, or workflow automation tools for data processing and transformations
• Practical experience cleaning, transforming, and validating real-world data
• Understanding of how data is used by automation systems, AI workflows, and decision logic
• Ability to think beyond reports and focus on data as system input
• Comfort working in ambiguous, evolving environments

• Work on AI-first data systems, not static dashboards
• Play a foundational role in Claro’s automation and intelligence stack
• High ownership and collaboration with AI and product teams
• Opportunity to grow into AI data, ML-ops, or intelligence roles
• Build systems that directly impact execution, efficiency, and sustainability

We are not looking for a traditional reporting-only data analyst. We are looking for someone who understands that good AI starts with good data, and wants to build data systems that machines can reason on.

If you enjoy working with real data, enabling AI workflows, and improving systems over time, we’d love to hear from you.