Senior Full Stack Data Engineer

We are hiring a senior-level Full Stack Data Engineer to build and scale the organization’s core data infrastructure.
This role requires a strong engineering-first mindset. The expectation is not limited to reporting or
analytics engineering. The individual will own end-to-end data architecture, scalable pipelines,
backend integrations, platform reliability, and AI-ready data foundations across healthcare operations.
The ideal candidate should be capable of operating independently, leading technical decisions,
handling production-scale systems, and driving execution with minimal supervision.
Key Responsibilities

• Design and build scalable batch and real-time data pipelines
• Build and maintain cloud-native data platforms
• Develop reliable ETL/ELT workflows across multiple systems
• Create robust backend integrations and APIs
• Enable operational, analytical, and AI use cases through clean data architecture
• Drive data quality, governance, observability, and monitoring
• Optimize pipeline performance, scalability, and cost
• Handle production debugging and incident resolution
• Mentor junior engineers and drive engineering standards
• Collaborate with product, operations, analytics, and leadership teams
  Mandatory Technical Skills
  Data Engineering
  Strong hands-on experience in:
• Python
• SQL
• Spark / PySpark
• Airflow
• Kafka
• Google Pub/Sub
• Message Queue systems (RabbitMQ / ActiveMQ / IBM MQ or equivalent)
• dbt
• Snowflake / BigQuery / Redshift
• PostgreSQL / MySQL
  Strong understanding of:
• ETL / ELT architectures
• Batch and streaming systems
• Data modeling
• CDC pipelines
• Schema evolution
• Data quality frameworks
• Distributed systems
• Parquet / Delta Lake / Iceberg
  Backend & Platform Engineering
  Must be comfortable building production-grade backend systems and integrations.
  Expected experience in:
• REST APIs
• FastAPI / Flask / Node.js
• Microservices architecture
• Async processing
• Queue-based systems
• Event-driven architectures
• Docker
• Kubernetes
• CI/CD pipelines
• GitHub Actions / Jenkins
• Terraform basics
  Cloud Infrastructure
  Strong experience in at least one cloud platform:
• AWS/ Azure/ GCP
• Experience with enterprise networking and infrastructure environments including Juniper
  ecosystems is preferred
  Expected capabilities:
• IAM and security
• Monitoring and logging
• Infrastructure debugging
• Cost optimization
• Production reliability
• Serverless and scalable architectures
  AI & Analytics Readiness
  Preferred exposure to:
• ML/AI data pipelines
• Feature engineering workflows
• Vector databases
• LLM/RAG architectures
• Real-time analytics
• Semantic layers
• Operational dashboards
  Preferred Background
  Strong preference for candidates from:
• Product companies
• SaaS platforms
• High-scale startups
• Healthcare tech organizations
• Data platform teams
• Healthcare domain experience is strongly preferred.
  Education Requirements
• B.Tech / BE in Computer Science, IT, or equivalent engineering disciplines.
• Candidates from strong engineering institutes preferred (IITs, NITs, BITS, IIITs, top-tier state
  engineering colleges)
  What We Are Looking For
  The candidate should demonstrate:
• Strong ownership mindset
• Deep engineering fundamentals
• Ability to solve ambiguous problems independently
• Production-scale systems thinking
• High execution capability
• Strong debugging and troubleshooting skills
• Leadership and mentoring ability
• Clear communication with cross-functional team