Data Engineer

About the Role

We are looking for a DataEngineer (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 senior role withopportunities to influence architecture, data strategy, and engineering best practices.

Key Responsibilities

Data & Backend Engineering

• Design, build, and maintain data-heavy backend systemsfor 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 PostgreSQLschema 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 Productteams 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.

Required Skills & Experience

Core Backend & Data Skills

• Strong experience with Pythonfor backend services and data processing.
• Proven ability to handle large-scale data ingestion, transformation, and transfer.
• Deep understanding of PostgreSQL, including performance tuning and working with large datasets.

Cloud & Infrastructure

• Hands-on experience with AWSservices such as S3, RDS (PostgreSQL), Lambda, ECS/Fargate, SQS/SNS, and CloudWatch.
• Experience designing cloud-native, scalable backend systems.
• Familiarity with data pipelines, batchjobs, and event-driven architectures.

Databases & Warehousing

• Experience with data-warehouse-style workloads, reporting, and historical data snapshots.
• Strong SQL skills and understanding of data modeling for both transactional and analytical use cases.

Security & Quality

• Understanding of data security, access control, and compliance-driven development.
• Experience with testing, monitoring, and maintaining production-grade systems.

Collaboration

• Comfortable working in agile, cross-functional teams.
• Strong communication skills and ability to take ownership of complex backend and data systems.