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+ youngest users in India to kickstart their financial journey super early in their life.
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 this Role:We are looking for a Data Engineer with 3-5 years of experience to build and maintain scalable data pipelines, optimize data infrastructure, and support real-time analytics in our fintech environment. This role requires strong expertise in big data processing and ClickHouse. The ideal candidate will work closely with cross-functional teams to design, develop, and deploy high-performance data solutions that drive business insights.
On the Job
- Build & Optimize Data Pipelines: Design, develop, and maintain scalable ETL workflows for processing structured and unstructured data.
- ClickHouse Expertise: Implement, optimize, and manage ClickHouse for efficient real-time analytics and reporting.
- Big Data Processing: Experience working with large-scale data architectures using Spark, Kafka, Hadoop, Flink or similar tools.
- Data Modeling & Warehousing: Design efficient data schemas, partitioning, and indexing strategies for optimal query performance.
- Real-Time Data Streaming: Implement streaming solutions using Kafka, Spark Streaming, or Flink to enable low-latency data processing.
- Cloud Data Infrastructure: Deploy and manage data solutions on AWS, GCP, or Azure with tools like S3, Redshift, BigQuery, or Snowflake.
- Automation & Monitoring: Develop robust monitoring systems and automate workflows using Airflow, Prefect, or Kubernetes.
- Data Security & Governance: Ensure compliance with GDPR, CCPA, and best practices for data integrity and security.
- Collaboration: Work closely with Data Scientists, Analysts, and Software Engineers to integrate data solutions into applications.
Must-haves (Min. qualifications)
- 3-5 years of experience in data engineering or related roles.
- Strong hands-on experience with ClickHouse for real-time data processing and analytics.
- Proficiency in Python, SQL, and familiarity with Scala or Java.
- Experience with Kafka, Spark, Hadoop, or Flink for big data processing.
- Expertise in ETL/ELT pipeline development and optimization.
- Hands-on experience with cloud-based data architectures (primarily AWS).
- Strong understanding of database performance tuning, indexing, and partitioning.
- Experience with workflow orchestration tools like Airflow etc.
- Solid understanding of SQL databases like Postgres and proficiency in writing SQL queries.
Good to have
- Experience working in the fintech domain or handling financial data.
- Knowledge of real-time data warehousing solutions.
- Hands-on experience with Kubernetes, Terraform, or Docker for data infrastructure.
- Familiarity with data observability tools for monitoring and debugging pipelines.
- Exposure to machine learning model deployment pipelines.
Why join us?
- Work on cutting-edge big data and real-time analytics in the fintech space.
- Opportunity to lead and scale high-impact data solutions.
- Collaborative, fast-paced, and growth-driven work environment.
- Competitive salary, benefits, and career growth opportunities.
