Fampay18d ago

Data Engineer - SDE 1

Bengaluru,BangaloreFull Timemid

Data EngineeringData EngineerDataData & AI

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Quick Summary

Requirements Summary

1–3 years in Data Engineering, specifically with distributed systems and cloud-native architectures. Coding: Expert-level Python/PySpark and SQL.

Technical Tools

Data EngineeringData EngineerDataData & AI

About Fam (previously FamPay)

Fam is India’s first payments app for everyone above 11. FamApp helps make online and offline payments through UPI and FamCard. We are on a mission to raise a new, financially aware generation, and drive 250 million+ young users in India to kickstart their financial journey super early in their life.

We’re reimagining how the next generation experiences fintech—going beyond payments to build a lifestyle brand that blends money, identity, and everyday experiences into one seamless, intuitive journey.

Founded in 2019 by IIT Roorkee alumni, Fam is backed by some of the most respected investors around the world like Elevation Capital, Y-Combinator, Peak XV (Sequoia Capital) India, Venture Highway, Global Founder’s Capital and the likes of Kunal Shah, Amrish Rao as angel investors.

About the Role

~1 min read

We are looking for a Data Engineer (SDE-1) to join our data team. The ideal candidate will be a play a key role to develop of high performant and scalable Data Lake-house, moving us toward a world of sub-minute data latency and unified batch/streaming compute. This is an engineering-heavy role where you will manage complex CDC flows, optimize distributed query engines and leverage AI to accelerate our development lifecycle.

Real-time CDC: Ownership of high-throughput ingestion from RDBMS to Lakehouse using Debezium, PeerDB.
Lakehouse Architecture: Designing and optimizing table formats (Iceberg, Delta, Hudi) for both performance and storage efficiency.
Unified Compute: Developing robust ETL/ELT frameworks in PySpark and Flink (handling both batch and streaming workloads).
Infrastructure & Ops: Managing data workloads on AWS (EMR, EKS, MSK, S3) and automating everything via Gitlab/Github Actions.
Query & BI: Tuning Trino or Clickhouse to power real-time dashboards in Metabase, Superset, and PowerBI.

Requirements

~1 min read

Experience: 1–3 years in Data Engineering, specifically with distributed systems and cloud-native architectures.
Coding: Expert-level Python/PySpark and SQL.
- Familiarity with Go/Java/Scala is a plus
Infrastructure: Hands-on experience with AWS (S3, EKS, MSK) and Infrastructure-as-Code.
Orchestration: Experience with Airflow or Temporal for complex workflow management.
AI-Native: Proficiency in using AI tools (Claude, Codex, Copilot) to write, test, and document code efficiently.
Systems Thinking: Ability to explain the trade-offs between different storage formats and processing frameworks.
Domain Modelling - Should be hands on in designing Domain models for OLAP like Fact, Dimension and types of SCD’s and OBT pattern tables.
Customer First - Interact with the Product & Key Stakeholders & help them by adding value to the business workflow with data & analytics.