About the Role
We are looking for a Data Engineer (Data & Cloud) to design, build, and operate large-scale, data-intensive systems in a healthcare domain. This role is heavily focused on data engineering, cloud infrastructure, and high-volume data movement, with hands-on ownership of backend services, pipelines, and storage systems.
The ideal candidate is strong in Python, AWS, PostgreSQL, and distributed data systems, with deep experience handling large datasets, batch and streaming workflows, and data warehouses.
This is a hands-on Lead role with opportunities to influence architecture, data strategy, and engineering best practices.
ey Responsibilities
Data & Backend Engineering
- Design, build, and maintain data-heavy backend systems for ingestion, processing, validation, and transformation of large healthcare datasets.
- Implement high-volume data transfer pipelines (batch and near-real-time) across internal systems, external partners, and cloud storage.
- Develop scalable backend services primarily using Python, following clean architecture and performance-first principles.
Cloud & AWS Architecture
- Build and operate systems on AWS, leveraging services such as S3, RDS (PostgreSQL), Lambda, ECS/Fargate, SQS/SNS, Glue, Athena, and CloudWatch.
- Design cloud-native solutions with a focus on scalability, reliability, fault tolerance, and cost optimization.
- Support serverless and containerized workloads for data processing and backend services.
Database & Data Storage
- Own PostgreSQL schema design, query optimization, indexing strategies, and performance tuning for very large tables.
- Work with analytical/data-warehouse-style workloads, including reporting, aggregations, and historical snapshots.
- Ensure data integrity, consistency, and lifecycle management across operational and analytical stores.
Data Security & Compliance
- Implement secure data handling practices including encryption at rest and in transit, access controls, and auditability.
- Work within healthcare data compliance expectations (HIPAA-aligned practices preferred).
- Ensure safe handling of PHI/PII across pipelines and services.
Observability & Reliability
- Implement logging, monitoring, and alerting using tools like CloudWatch, Sentry, and custom metrics.
- Debug and resolve complex production issues related to data processing, performance, and scalability.
Collaboration & Continuous Improvement
- Work closely with DevOps, Data Engineering, QA, and Product teams to deliver reliable systems.
- Participate in architectural discussions, code reviews, and technical decision-making.
- Mentor junior engineers and promote best practices in data and backend engineering.
Pay: ₹3,500,000.00 - ₹4,000,000.00 per year
Benefits:
- Flexible schedule
- Food provided
- Health insurance
- Leave encashment
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund
- Work from home
Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)
