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 new 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, workplace provisioning, data sanitization) - Establish and enforce code quality standards including linting, formatting, and review workflows across data platform repositories

📌 Data Engineer - Contract (Mail at nirmal.francis@ (Chennai)
🏢 Inspire
📍 Chennai