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Careers @ Revfin

Data Engineer

We seek a Data Engineer with deep expertise in handling large-scale IoT data and building secure, optimized systems for digital lending. You will work on data pipelines, enforce data governance/compliance, and optimize databases/queries while working with Kafka, ClickHouse, S3, Redis, Mage AI, Apache Airbyte, MongoDB, Apache Superset, and Power BI. Proficiency in Python, Node.js, Java, or C# is critical for server-side logic and integrations.
Key Responsibilities
IoT & Financial Data Pipeline Engineering
  • Design high-throughput, low-latency data pipelines for IoT telemetry (sensors, devices) and digital lending transactions using Kafka (streaming) and Mage AI, Apache Airbyte ( any industry standard ETL platform).
  • Implement anonymization, masking, and encryption for sensitive financial and IoT data at rest and in transit.
  • Optimize data ingestion/storage for time-series IoT data in ClickHouse and MongoDB, ensuring scalability to handle TB+/PB-scale datasets.
Database Optimization & Query Tuning
  • Design developer highly optimized databases (OLAP, SQL/NoSQL) for IoT time-series data and lending transactions.
  • Write and optimize complex SQL queries (window functions, joins) for ClickHouse to support real-time analytics.
  • Use Redis for caching high-frequency queries and reducing latency in API/dashboard interactions.
Server-Side Programming & Integrations
  • Develop and maintain data APIs and microservices in Node.js, Java, or C# to expose data to internal/external systems.
  • Build data validation scripts (Python) and automate workflows with Mage AI.
  • Integrate with third-party systems (credit bureaus, IoT device APIs) while ensuring data integrity.
Data Visualization & Collaboration
  • Create real-time dashboards in Apache Superset and Power BI to monitor IoT device health, loan performance, and risk metrics.
  • Partner with DevOps to implement CI/CD pipelines for data infrastructure.
Security, Compliance & Governance
  • Enforce GDPR, CCPA, and financial regulatory standards (e.g., PCI-DSS) through data masking, role-based access, and audit trails.
  • Collaborate with business and security teams to design data access. retention policies and compliance frameworks.
  • Implement row-level security in databases (e.g., ClickHouse) and BI tools (Power BI, Superset).
Key Skills:
  • Databases: ClickHouse (optimization, sharding), MongoDB (aggregation pipelines), Redis.
  • Languages: Python (Pandas, PySpark), SQL (advanced), and one server-side language (Node.js, Java, C#).
  • Data Security: Anonymization (e.g., tokenization), encryption (AWS KMS, TLS), compliance (GDPR).
  • Tools: Kafka (consumer/producer tuning), Airbyte, Mage AI, S3.
  • Proven ability to optimize complex queries (e.g., subqueries, indexing strategies) and troubleshoot performance bottlenecks.
  • Experience with time-series data (IoT) and financial data (digital lending, transactions).
Qualification and Experience:
  • Bachelor’s/Master’s in Computer Science, Data Engineering, or related field.
  • 4+ years of experience in data engineering, with 2+ years in IoT/high-volume data environments.
Application Process
Interested candidates should submit their resume and a brief cover letter highlighting relevant experience at akansha.gupta@revfin.in or neha.sharma@revfin.in.
Details
New Delhi
4+ years of Experience Required
Working Hours
Monday-Friday (9.30 a.m to 6 p.m)
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