Data Engineer

Role:

Experience:

Location:

Engagement:

Work Type:

About the Role

Data Engineer

Pharma or Life Sciences

Key Responsibilities

Cloud Data Engineering

• Design, build, and optimize scalable data pipelines across AWS, Azure, or GCP.
• Develop ingestion, transformation, and orchestration pipelines using cloud-native services (e.g., AWS Glue, Azure Data Factory, GCP Dataflow).
• Implement ETL/ELT workflows for large-scale structured and unstructured datasets.

CI/CD, Cloud Build & Deployment

• Build and maintain

  CI/CD pipelines

  for infrastructure and application deployments.
• Work with

  Azure DevOps, GitHub Actions, GitLab CI, Jenkins, or Google Cloud Build

  .
• Ensure automated deployments, version control, and environment consistency.

Infrastructure as Code (IaC)

• Use

  Terraform

  to design, provision, and manage cloud infrastructure.
• Implement reusable IaC modules for multi-cloud data architecture.

Cloud Architecture & Operations

• Work across

  AWS, Azure, and GCP

  to build secure, scalable, and cost-efficient data platforms.
• Collaborate with architecture teams on network, security, IAM, and storage configurations.
• Optimize data workflows for performance, cost, and reliability.

Data Integration & Analytics Support

• Build data models, pipelines, and transformations to support analytics, ML, and reporting needs.
• Work with Data Scientists, BI teams, and domain experts to ensure data availability and quality.

Documentation & Collaboration

• Maintain clear technical documentation covering pipelines, architecture, and workflows.
• Collaborate with cross-functional teams including cloud engineering, QA, and domain SMEs.

Required Skills

• 6–12 years of experience as a Data Engineer in cloud-driven environments.
• Strong hands-on experience with at least

  one

  of the following cloud platforms:

• AWS

  (Glue, Lambda, S3, EMR, Redshift)

• Azure

  (ADF, Synapse, Databricks, Storage, Functions)

• GCP

  (BigQuery, Dataflow, Cloud Build, Cloud Functions)
• Strong experience with

  CI/CD pipelines

  (Azure DevOps, GitHub Actions, Jenkins, GCP Cloud Build).
• Solid expertise in

  Terraform

  for IaC.
• Strong Python or SQL experience for building data pipelines.
• Experience with data modeling, ETL/ELT patterns, and distributed data processing.
• Exposure to infrastructure and application deployment automation.

Good-to-Have Skills

• Pharma / Life Sciences domain experience.
• Experience with DataOps practices.
• Familiarity with regulatory and compliance requirements (GxP, HIPAA preferred).
• Experience with containerization (Docker, Kubernetes).