Data Engineer

Role : Data Engineer

Experience : 6–12 years

Location : Remote

Engagement : Contract (4–6 Months)

Work Type : Remote

About the Role

We are seeking an experienced Data Engineer to support data modernization and analytics initiatives across multi-cloud environments. The ideal candidate has a strong background in building scalable data solutions on AWS, Azure, or GCP , along with hands-on expertise in CI / CD pipelines, infrastructure automation using Terraform, and cloud-native data engineering practices .

Experience working in Pharma or Life Sciences environments is a strong plus (not mandatory).

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).