What You'll Do

● Design, build, and operate production-grade ETL pipelines that move data from source systems into our lake and warehouse, using a medallion architecture (bronze, silver, and gold layers)

● Own our SQL based operational data, including designing reliable CDC (change data capture) patterns to stream it into the data lake

● Build and maintain our data lake and data warehouse, modelling schemas that data scientists and analysts can query with confidence

● Orchestrate pipelines using Airflow (Amazon MWAA) and manage transformations with dbt, with robust testing, documentation, and data quality checks built in

● Provision and manage AWS infrastructure using Infrastructure as Code, covering compute, storage, networking, and security for the data platform

● Containerize data and platform services with Docker and run them on ECS or EKS, with CI/CD pipelines that ship changes safely and often

● Monitor pipeline health, data quality, and cloud cost, building alerting and observability so issues surface before they become production incidents

● Provide occasional support to the data science team's ML and MLOps infrastructure: feature store integration, model serving endpoints, and access to production data

● Partner with data scientists and analysts to understand data needs and translate them into reliable, well-documented pipelines and datasets

● Champion data security, privacy, and compliance across the platform, including proper handling of PHI and PII in a healthcare context

What You'll Bring

● 3 to 5 years of experience in data engineering, cloud engineering, or a combined infrastructure and data role

● Hands-on production experience with AWS: S3, Redshift, RDS/Aurora, IAM, VPC networking, and either ECS or EKS

● Strong SQL skills, with real-world PostgreSQL experience (schema design, performance tuning, CDC)





● Experience building and operating ETL/ELT pipelines with tools like Airflow, dbt, AWS Glue, or Spark

● Practical experience with medallion (bronze/silver/gold) or similar layered lakehouse architectures

● Proficiency with Infrastructure as Code, ideally Terraform, for provisioning and managing cloud resources

● Experience with Docker and container orchestration (ECS, EKS, or Kubernetes)

● Working knowledge of CI/CD pipelines and DevOps practices (GitHub Actions, CodePipeline, or similar)

● Strong Python or similar scripting skills for pipeline development and automation

● Understanding of data security, access control, and compliance considerations, ideally including healthcare data (HIPAA and PHI)

● Comfort working across the stack, from writing a transformation in dbt to debugging a networking issue in a VPC

Nice to Have (Bonus Points)

● AWS certifications are a strong plus, for example AWS Certified Solutions Architect Associate or AWS Certified Data Engineer Associate

● Experience supporting ML/MLOps infrastructure: feature stores, model serving, or ML pipeline orchestration

● Exposure to streaming data tools (Kafka, Kinesis, or Flink)

● Experience with Snowflake or Databricks alongside or instead of Redshift

● Familiarity with healthcare data standards and interoperability (HL7, FHIR, EHR/EMR systems)

● Deeper Kubernetes experience (CKA/CKAD-level skills)

Tools & Tech You'll Work With

Languages: Python, SQL

Databases: PostgreSQL (RDS/Aurora), Amazon Redshift

Data Lake/Platform: Amazon S3, medallion architecture (bronze/silver/gold), [Delta Lake or Iceberg]

Orchestration/Transform: Airflow (Amazon MWAA), dbt, AWS Glue

IaC/Cloud: Terraform, AWS (S3, Redshift, RDS, IAM, VPC, ECS/EKS)

Containers/CI-CD: Docker, ECS or EKS, GitHub Actions or AWS CodePipeline

Monitoring: [CloudWatch, Datadog, or similar]

📌 Data Engineer & Cloud Engineer (Secunderabad)
🏢 Denuo Source India Private
📍 Secunderabad