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AWS Data Platform Architect (AI & Graph)

Thermofisher thermofisher.com Open
Bangalore Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Thermofisher. Bangalore · full-time.

Pay not stated Data Engineering salary

RoleData Engineering
SeniorityMid-level
LocationBangalore
EmploymentFull-time
PostedOct 30, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Shape the AWS platform across data ingestion, storage, transformation, semantic access and consumption
  • Build RAG and other LLM access patterns, then test them through proofs of concept before production use
  • Create graph models for relationship-focused analysis and connect them to enterprise analytics
  • Oversee Redshift, Databricks and Athena performance, workload governance and cost, while protecting current reporting
  • Set governance and security controls, document architecture decisions, and guide engineering and analytics teams

What you bring

  • A relevant bachelor's degree and at least ten years in data architecture, data engineering or cloud data platforms
  • A record of designing and operating enterprise data platforms on AWS
  • Production experience with Redshift, Databricks, Athena and Power BI, plus strong SQL and Python skills
  • Experience building graph data models or working with graph databases

Who this fits

This suits a hands-on architecture lead who can guide technical direction while working deeply with data platforms, SQL and Python. The role is based in Bangalore, India, and follows a standard Monday-to-Friday schedule. It includes leadership through standards, reviews and guidance, alongside individual technical work.

From the employer

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

Position Summary

We are seeking an experienced AWS Data Platform Architect to own and evolve our enterprise data platform. This role is responsible for designing a scalable, secure, and governed AWS-based data architecture that supports both current analytics and an AI-ready Data-as-a-Platform foundation.


You will ensure the platform is AI-ready by design, embedding capabilities such as RAG patterns, semantic access, and graph-based data modeling, while maintaining operational stability of existing analytics workloads across Redshift, Databricks, Athena, and Power BI.


This is a hands-on architecture leadership role that requires deep expertise in SQL, Python, and modern data platforms, with end-to-end ownership of data, analytics, and platform governance.


Key Responsibilities

Platform Architecture & Strategy

  • Define and evolve the target AWS data platform architecture across ingestion, storage, transformation, semantic, and consumption layers
  • Establish and enforce architecture standards for scalability, security, reliability, and cost efficiency
  • Design integration and migration patterns across legacy and modern platforms (Redshift, Databricks, Athena, Power BI/Fabric, and semantic layers such as Cube/SPOT where applicable)
  • Ensure platform evolution introduces new capabilities without disrupting existing reporting and analytics workloads

AI & Graph Enablement

  • Design and implement AI/LLM-ready architecture patterns, including RAG-based retrieval and semantic data access
  • Develop and integrate graph data models to support relationship-driven analytics and intelligence use cases
  • Ensure the platform supports efficient data access patterns for AI workloads, across structured, semi-structured, and graph data
  • Lead proofs-of-concept and reference implementations to validate AI and graph capabilities prior to production adoption

Platform Ownership & Optimization

  • Provide architectural oversight for Redshift, Databricks, and Athena, ensuring performance optimization, workload governance, and cost efficiency
  • Guide and review complex SQL transformations and workloads, ensuring scalability and performance across large datasets
  • Ensure Power BI and semantic layers are aligned to governed, high-quality datasets
  • Identify and resolve architecture-level bottlenecks impacting performance, cost, or reliability
  • Maintain architecture documentation, standards, and technical decision records

Governance, Security & Operations

  • Implement and enforce data governance standards, including dataset certification, access control, and usage consistency
  • Define and manage IAM roles, encryption, and security controls across AWS environments
  • Ensure production stability through structured rollouts, validation, and change management practices
  • Monitor and continuously optimize platform performance and cost efficiency

Leadership & Collaboration

  • Drive adherence to architectural best practices across engineering and analytics teams through standards, reviews, and guidance
  • Translate business and analytics requirements into scalable, future-ready technical designs
  • Partner with Data Engineering, BI, and platform teams to ensure consistent implementation across all layers
  • Support technical capability building through documentation, reviews, and knowledge sharing

Qualifications

Required

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 10+ years of experience in data architecture, data engineering, or cloud data platforms
  • Proven experience designing and operating AWS-based enterprise data platforms
  • Hands-on expertise with Redshift, Databricks, Athena, and Power BI in production environments
  • Strong proficiency in SQL and Python, enabling development, optimization, and troubleshooting of data pipelines, queries, and cross-platform integrations
  • Experience designing and implementing graph data models or graph databases
  • Experience enabling or integrating AI/LLM use cases within data platforms

Core Skills

  • AWS architecture and cloud-native data design principles
  • Advanced SQL expertise, including query optimization, data modeling, and performance tuning on large-scale datasets
  • Performance optimization across modern data platforms (Redshift, Databricks, Athena)
  • Data governance and security, including IAM, access controls, and encryption
  • Graph modeling and relationship-driven data design
  • Batch and real-time data processing patterns
  • Strong troubleshooting and system-level performance tuning
  • Clear and structured architecture documentation and decision records

Preferred

  • Experience implementing CI/CD for data platforms
  • AWS Professional-level certifications
  • Familiarity with RAG architectures and LLM-driven data access patterns

What You’ll Drive

  • Evolution of a modern, unified AWS data platform aligned to a Data-as-a-Platform model
  • Adoption of AI-ready data architecture, including RAG and semantic access patterns
  • Integration of graph-based modeling into enterprise analytics and intelligence use cases
  • Improved performance, governance, and cost efficiency across the data ecosystem

Why This Role Matters

This role sits at the intersection of data platform architecture and next-generation AI enablement. You will shape how data is structured, accessed, and leveraged to support advanced analytics, intelligent applications, and scalable AI use cases, while ensuring the reliability and continuity of the existing data ecosystem.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.