Data Analyst

Role: Data Analyst

Industry: Fintech, AI

Location: Bangalore (Hybrid)

Type: Full-time

Experience: 2-5 years

About the company

The company is an early-stage, venture-backed, AI-first finance technology company redefining how high-volume businesses run their finance operations. Instead of stitching together legacy, manual tools, it is building an intelligent finance operating system that centralizes data, automates reconciliation, streamlines payouts and collections, and delivers real-time results

Role Overview

• Own complex SQL: write, review, and optimize queries across large, sometimes messy datasets (billions of rows) for analysis and production use.
• Build reliable data pipelines and analyses in Python (pandas/pySpark where needed); automate recurring workflows and QC checks.
• Translate ambiguous business questions into measurable analyses, experiments, and metrics; tell the story with clarity.
• Develop and maintain clean, well-documented datasets, views, and dashboards (e.g., dbt/Looker/Power BI/Tableau).
• Investigate anomalies and data-quality issues; implement guardrails, tests, and alerts to prevent recurrence.
• Partner with Product, Ops, and Engineering to define KPIs, run deep-dives, and deliver actionable recommendations.
• Improve performance: index/partition/tune queries, profile data, and benchmark transformations.
• Uphold best practices for version control, reproducibility, and code review in analytics.

What You'll Bring (Must-Haves)

• Exceptional SQL: expert at window functions, CTEs, complex joins, subqueries, performance tuning, and query optimization.
• Fluency in Python for data analysis/automation (pandas, numpy; familiarity with notebooks; writing modular, testable code).
• Proven experience analyzing large-scale datasets (row counts in the hundreds of millions+ or multi-TB) and delivering business insights.
• Understanding of data modeling skills (star/snowflake), and ETL/ELT concepts, and cloud data warehouses (e.g., Snowflake/BigQuery/Redshift).
• Meticulous attention to detail with a bias for validating assumptions, reconciling numbers, and documenting logic.
• Ability to turn findings into clear narratives and visuals for technical and non-technical audiences.
• 25 years in a data analyst/analytics engineer role or equivalent.

Nice-to-Haves

• Experience with dbt, Airflow, Dagster, or similar orchestration/testing tools.
• Exposure to PySpark or distributed compute frameworks.
• Dashboarding in Looker/Power BI/Tableau and semantic modeling (LookML/DAX).
• Comfort with experimentation (A/B testing, basic statistical inference) and cohort/retention analysis.

What We Offer

• Career velocity: Shape the architecture, influence roadmap, and grow into leadership.
• Real impact: Ship fast, see your work power critical business operations.
• Work with a founding team of repeat entrepreneurs and technology leaders backed by top-tier VCs.
• Enjoy autonomy, high velocity, a product-first culture, and global ambition.
• Receive competitive salary and ESOPs for meaningful ownership.
• Flexible work culture, 3 days work from office