Role Description:

- Cloud Infrastructure Architecture (AWS)
- Architect, deploy, and manage scalable AWS data infrastructure including Redshift, S3, Lambda, IAM, VPC, and related services

- Define and enforce infrastructure-as-code standards and CI/CD practices for all data platform components

- Monitor infrastructure health, optimize performance, and drive cost efficiency across cloud resources

- Ensure high availability and disaster recovery posture for all critical data systems

- Manage multi-account AWS environments with cross-account IAM roles, VPC peering, and environment-specific security boundaries (dev, test, production)

- Data Warehouse Design &
- Development

- Architect and evolve the organization’s Redshift data warehouse using dimensional modeling (Kimball methodology) and star schema best practices

- Architect and engineer the dbt project end-to-end: data modeling, testing, documentation, and deployment via Jenkins across development, testing, and production environments

- Write complex, optimized SQL and Python to build and maintain production data models, snapshots, and incremental loads

- Establish and enforce data modeling standards, naming conventions, and development workflows

- Data Pipelines &

- Integrations

- Design and build robust ELT/ETL pipelines using custom Python and managed connectors via Fivetran

- Manage third-party data integrations including SaaS platforms, APIs, and partner data feeds

- Implement pipeline observability, alerting, and data quality frameworks to ensure reliable data delivery

- Evaluate and adopt recent ingestion tools and patterns as the data ecosystem evolves

- Data Security &

- Compliance

- Own data platform security including IAM roles and policies, Redshift access controls, encryption at rest and in transit, and network security (VPC, security groups)



in partnership with Infrastructure

- Ensure compliance with HIPAA, SOC 2, and applicable healthcare data privacy regulations

- Conduct regular access reviews, security audits, and vulnerability assessments of the data ecosystem

- Partner cross-functionally to implement and maintain data governance standards

- Design, implement and maintain PII anonymization pipelines to provision safe, production-representative data to development and test environments

- Identify and automate recurring compliance workflows (e.g., data deletion requests) to ensure consistent adherence to GDPR and other applicable privacy regulations at scale

- Platform Reliability &

- Availability

- Define and maintain SLAs for the data platform, proactively identifying and resolving availability risks

- Lead incident response and root cause analysis for data platform outages or degraded performance

- Build and maintain runbooks, architecture documentation, and operational playbooks

- Lead legacy system migrations with minimal disruption, including data warehouse migrations, pipeline platform transitions, and infrastructure modernization initiatives

- Technical Leadership &

- Collaboration

- Serve as a technical mentor and escalation point for data analytics and AI/ML engineering team members

- Collaborate with Data Analytics, AI/ML Engineering, Infrastructure, Product, and Software Engineering teams to align infrastructure with roadmap priorities

- Contribute to architecture reviews and technology evaluations

- Developer Experience &

- Tooling

- Build and maintain internal developer tooling to automate operational tasks (e.g., permission management, environment provisioning, data sanitization)

- Establish and enforce code quality standards including linting, formatting, and review workflows across data platform repositories

📌 Data Engineer - Contract (Mail at [email protected]) (Chennai)
🏢 Inspire
📍 Chennai