Data Analyst

About the job: We are seeking a Data Analyst to join us. The person in this role will be an integral part of a fast-moving, ownership-driven team, embedded with a major African fintech client's consumer business. This is a hands-on, learning-intensive, execution-oriented role with strong coaching and mentorship built in. The work is about turning data into decisions : surfacing early signals and answering \"so what do we do,\" not just building dashboards. This role is based in our Hyderabad office (on-site). About us: We're a new age tech & analytics services company. We're HQ'ed in Hyderabad with clients across the world. Initial Responsibilities TL;DR: Merge product and business data into decision-ready views for a fintech client, working directly with a senior operator, with senior analysts coaching you along the way. Build and ship analysis on a client engagement, working alongside senior team members from question to insight Merge product analytics and business-performance data into a single view people actually act on, replacing slow, manual reporting with automated pipelines Write clean, efficient SQL and build clear, decision-oriented dashboards in Power BI; work with product analytics / CDP-style data Own your work end-to-end: validate the numbers, catch early signals before they become problems, present findings, and raise the quality bar over time Take coaching seriously and sharpen fundamentals in analytics, business reasoning, and data storytelling, collaborating directly with the founder, senior analysts, and the client's GM Qualifications TL;DR: Strong SQL and analytical fundamentals are non-negotiable.

Tools can be learned, but you should bring genuine commercial curiosity and the ability to figure things out. You Are: 2 to 4 years into your analytics journey, internships included Curious and self-motivated, humble enough to take feedback and sharp enough to act on it Someone who thinks in margins, drivers, and risk — not just queries — and can show analysis you've owned end-to-end Must-haves: SQL (writing efficient queries, working across relational data) Writing clean Python code for analysis and automation Power BI (data modeling, building dashboards people actually use) Analytical fundamentals: framing a business question, structuring an analysis, validating data, and communicating a clear \"so what\" Nice-to-haves: Product analytics / CDP-style tools (Amplitude, Mixpanel, Segment, or similar) Fintech / payments domain exposure