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