AWS Data Platform Architect

Job Description

Role Overview:You are sought after for the position of AWS Data Platform Architect at Thermo Fisher Scientific. Your main responsibility will be to design and oversee the development of an enterprise data platform on AWS that is scalable, secure, and supports analytics as well as an AI-ready Data-as-a-Platform foundation. You will be hands-on in your approach as an architecture leader, requiring expertise in SQL, Python, and modern data platforms.Key Responsibilities:- Define and evolve the target AWS data platform architecture, including 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 like Redshift, Databricks, Athena, Power BI/Fabric, and semantic layers- Ensure platform evolution introduces new capabilities without disrupting existing reporting and analytics workloads- 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- Lead proofs-of-concept and reference implementations to validate AI and graph capabilities prior to production adoption- Provide architectural oversight for Redshift, Databricks, and Athena, ensuring performance optimization, workload governance, and cost efficiency- Guide and review complex SQL transformations and workloads to ensure scalability and performance across large datasets- 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- 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 sharingQualification Required:- Bachelors degree in Computer Science, Engineering, or related field- 8 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 Role Overview:You are sought after for the position of AWS Data Platform Architect at Thermo Fisher Scientific. Your main responsibility will be to design and oversee the development of an enterprise data platform on AWS that is scalable, secure, and supports analytics as well as an AI-ready Data-as-a-Platform foundation. You will be hands-on in your approach as an architecture leader, requiring expertise in SQL, Python, and modern data platforms.Key Responsibilities:- Define and evolve the target AWS data platform architecture, including 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 like Redshift, Databricks, Athena, Power BI/Fabric, and semantic layers- Ensure platform evolution introduces new capabilities without disrupting existing reporting and analytics workloads- 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- Lead proofs-of-concept and reference implementations to validate AI and graph capabilities prior to production adoption- Provide architectural oversight for Redshift, Databricks, and Athena, ensuring performance optimization, workload governance, and cost efficiency- Guide and review complex SQL transformations and workloads to ensure scalability and performance across large datasets- 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 performanc

Keyskills :
SQLPythonAWSAthenaPower BIData ArchitectureData EngineeringRedshiftDatabricksCloud Data Platforms