About FuelBuddy is a B2B fuel delivery company scaling automated fuel logistics across the UAE, Mozambique, Zambia, Zimbabwe, and Nigeria. We run a large automated bowser fleet that delivers fuel directly to enterprise customers across logistics, retail, construction, and industrial sectors, replacing the traditional petrol-station model with an on-demand, IoT-driven alternative that is measurably faster, safer, and more accountable for the businesses that depend on it. Our international tech team is building the software platform that powers this operation end-to-end from the CRM and ERP that handle sales and finance, to the dispatch engine that plans daily deliveries, to the IoT automation running on the bowsers themselves, to the customer and operations dashboards that enterprises and our own teams use every day.

The international stack is built on Vue 3, Node.js/Fastify, PostgreSQL, Hasura GraphQL, ERPNext (Frappe), and GCP, with BigQuery powering cross-market analytics across all five countries.

Role summary You will be the second hire into FuelBuddy's Data pod, working directly under the Senior Data Analyst who is building our reporting layer from zero.

This is a rare seat: instead of inheriting a mature warehouse and picking up ticket queues, you will help build the warehouse itself — writing the models, defining the metrics, and shipping the dashboards that five country operations run on. Expect roughly 60% of your time on recurring reporting and dashboard delivery, and 40% on ad-hoc analysis for operations, finance, and leadership. You will be given real ownership early — specific dashboards, specific metrics, specific data-quality domains — with close review and mentoring from the Senior Analyst rather than a hands-off sink-or-swim.

What you will do Write and maintain SQL in BigQuery to answer operational questions across dispatch, fleet, credit, and revenue Build and maintain dashboards in Looker Studio or Metabase for operations, finance,



and country leadership teams Own the daily and weekly recurring reporting cycle — making sure numbers land on time, tie out, and are explainable Take ad-hoc questions from business stakeholders, clarify what is actually being asked, and deliver a clean answer with the caveats stated Support the Senior Analyst in building data models in the warehouse — contributing transformations, tests, and documentation as our modelling layer matures Investigate data-quality issues, trace them back to source systems (ERPNext, dispatch, IoT), and raise them with the Backend and ERP pods instead of patching them downstream Automate repetitive reporting and reconciliation work with Python so it stops consuming analyst hours Document metric definitions so that "litres dispensed" or "truck utilisation" means the same thing in every country and every dashboard Must-have skills Advanced SQL — joins, aggregations, CTEs, window functions, and the ability to debug a query that returns the wrong number rather than just one that errors Python for analytics — pandas and notebooks; comfortable writing a script that cleans, joins, and outputs a dataset without hand-holding Strong Excel — pivots, lookups, and the judgement to know when a problem has outgrown a spreadsheet Hands-on exposure to a BI tool — Looker Studio, Metabase, Power BI, or Tableau; you have built and shipped dashboards that other people actually used Explicit written communication — you can explain what a number means, where it came from, and what it does not prove Attention to detail and healthy scepticism about your own output — you sanity-check a result before sending it Good to have dbt — any exposure to models, tests,



or documentation Experience with a cloud data warehouse (BigQuery, Snowflake, Redshift) Basic data modelling concepts — fact and dimension tables, star schemas Git and version-controlled analytics work Exposure to ERPNext or any ERP data model Familiarity with logistics, fleet, or energy KPIs (litres dispensed, cost per litre, credit days outstanding, truck utilisation) Who this role is for This is the right role for an analyst who has done one or two years of dashboard and reporting work and now wants to learn how a proper analytics stack is designed — modelling, testing, and metric governance — rather than staying in a request-queue job. You will get direct mentoring from a senior analyst building the function from scratch, and visible ownership across five markets within your first year. It is the wrong role if you want a fully defined process on day one, or prefer to stay strictly within a single dashboard tool.

What success looks like in 12 months You independently own a defined set of operational dashboards and the recurring reporting cycle around them, with the Senior Analyst reviewing rather than rebuilding your work. You are contributing models and tests to the warehouse, not just querying it. Business stakeholders come to you directly for their questions, and the recurring reports that used to be assembled manually in Excel now run themselves.

Benefits & perks Claude Code for the data team. Every member of the technology team gets a seat on Anthropic's Claude for Teams from day one, including Claude Code in the terminal. We invest in tooling that makes you more effective, not just busier — and we expect you to use it well.

Comprehensive health insurance. Full medical cover for you from your first day, no waiting period. Generous work-from-home policy. We trust our team to work from where they do their best thinking. Our hybrid model leans heavily towards flexibility, with only the minimum in-office time needed for collaboration and team rituals

📌 Junior Data Analyst (Gurugram)
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