Role & responsibilities

Data Pipeline Development
Design and implement robust, scalable data pipelines using our contemporary data stack
Build real-time streaming pipelines with Kafka and Change Data Capture (CDC)
Develop batch processing workflows for data transformation and analytics
Implement data quality frameworks and monitoring systems

Infrastructure & Architecture
Architect and maintain our data lake infrastructure using Apache Iceberg
Optimize data storage and retrieval across multiple data stores (PostgreSQL, Snowflake, ClickHouse)
Design partitioning and sharding strategies for high-volume datasets.
Data Integration & CDC
Set up and maintain Change Data Capture (CDC) pipelines using Debezium
Build real-time data synchronization between operational and analytical systems
Handle schema evolution and ensure backward compatibility
Implement idempotent data processing patterns
Performance Optimization
Optimize query performance across different data engines
Implement productive data compression and storage strategies
Design and maintain data indexing strategies
Monitor and troubleshoot performance bottlenecks
Collaboration & Leadership
Collaborate with data scientists, analysts, and product teams




Mentor junior engineers and contribute to technical decision-making
Participate in code reviews and maintain high engineering standards
Document architectures, processes, and best practices

Preferred candidate profile

Advanced Technical Experience
Experience with multiple cloud providers (AWS, GCP, Azure)
Hands-on experience with Apache Iceberg in production environments
Experience with data mesh or federated data architectures
Knowledge of machine learning pipelines and feature stores
Experience with data quality tools (Excellent Expectations, Deequ, etc.)

Leadership & Collaboration
Experience mentoring junior engineers or leading technical initiatives
Robust communication skills with both technical and non-technical stakeholders
Experience working in agile development environments
Track record of improving data engineering practices and standards

Industry Experience
Experience in relevant industry: fintech, e-commerce, SaaS, etc.
Understanding of regulatory requirements (GDPR, SOX, PCI, etc.)

Experience with A/B testing and experimentation platforms

📌 Data Engineer Mumbai (India)
🏢 Insync Analytics
📍 India