Job Description

Role Description:

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- Cloud Infrastructure Architecture (AWS)
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- Architect, deploy, and manage scalable AWS data infrastructure including Redshift, S3, Lambda, IAM, VPC, and related services
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- Define and enforce infrastructure-as-code standards and CI/CD practices for all data platform components
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- Monitor infrastructure health, optimize performance, and drive cost efficiency across cloud resources
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- Ensure high availability and disaster recovery posture for all critical data systems
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- Manage multi-account AWS environments with cross-account IAM roles, VPC peering, and setting-specific security boundaries (dev, test, production)
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- Data Warehouse Design & Development
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- Architect and evolve the organization's Redshift data warehouse using dimensional modeling (Kimball methodology) and star schema best practices
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- Architect and engineer the dbt project end-to-end: data modeling, testing, documentation, and deployment via Jenkins across development, testing, and production environments
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- Write complex, optimized SQL and Python to build and maintain production data models, snapshots, and incremental loads
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- Establish and enforce data modeling standards, naming conventions, and development workflows
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- Data Pipelines & Integrations
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- Design and build robust ELT/ETL pipelines using custom Python and managed connectors via Fivetran
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- Manage third-party data integrations including SaaS platforms, APIs, and partner data feeds
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- Implement pipeline observability, alerting, and data quality frameworks to ensure reliable data delivery
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- Evaluate and adopt new ingestion tools and patterns as the data ecosystem evolves
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- Data Security & Compliance
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- 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
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- Ensure compliance with HIPAA, SOC 2, and applicable healthcare data privacy regulations
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- Conduct regular access reviews, security audits, and vulnerability assessments of the data ecosystem
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- Partner cross-functionally to implement and maintain data governance standards
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- Design, implement and maintain PII anonymization pipelines to provision safe, production-representative data to development and test environments
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- Identify and automate recurring compliance workflows (e.g., data deletion requests) to ensure consistent adherence to GDPR and other applicable privacy regulations at scale
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- Platform Reliability & Availability
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- Define and maintain SLAs for the data platform, proactively identifying and resolving availability risks
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- Lead incident response and root cause analysis for data platform outages or degraded performance
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- Build and maintain runbooks, architecture documentation, and operational playbooks
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- Lead legacy system migrations with minimal disruption, including data warehouse migrations, pipeline platform transitions, and infrastructure modernization initiatives
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- Technical Leadership & Collaboration
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- Serve as a technical mentor and escalation point for data analytics and AI/ML engineering team members
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- Collaborate with Data Analytics, AI/ML Engineering, Infrastructure, Product, and Software Engineering teams to align infrastructure with roadmap priorities
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- Contribute to architecture reviews and technology evaluations
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- Developer Experience & Tooling
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- Build and maintain internal developer tooling to automate operational tasks (e.g., permission management, environment provisioning, data sanitization)
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- Establish and enforce code quality standards including linting, formatting, and review workflows across data platform repositories
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📌 Data Engineer - Contract (Mail at nirmal.francis@ (Tamil Nadu)
🏢 Inspire
📍 Tamil Nadu