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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Staff IT Architect - **Company:** Thermofisher Scientific - **Location:** Carlsbad, CA, United States - **Experience:** Expert - **Salary:** $143,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Automated Storage and Retrieval Systems, Microsoft Azure, Cloud Computing, Cloud Computing Security, Cloud Database, Software Documentation, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Software Debugging, Github, Identity and Access Management, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Power BI, Azure Data Lake, SQL Databases, Data Streaming, Azure Service Bus, Data Processing, Cloud Platform System, Multi-Cloud, Microsoft Fabric, Data Lakes, AI Platforms, Pyspark, Information Technology, Data Lineage, Data Analytics, Apache Kafka, Spark Streaming, Data Management, Virtual Agents, Functional Programming, Terraform, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** May 14, 2026 - **Apply:** https://dejobs.org/x/x/7ECE6FE4819847EDB58E03F473226425/job/ ## About the Role * Over 8 years of expertise in data architecture, data engineering, or cloud-based data/AI solutions. * BS/MS or equivalent experience in Computer Science, Information Systems, or a related field. * Shown proficiency in multi-cloud solutions (AWS and Azure), encompassing S3, Redshift, Glue, Lambda, Kinesis, Azure Data Lake, Synapse Analytics, and Fabric. * 3+ years working with Databricks and/or Fabric Lakehouse, developing scalable data pipelines, improving Delta Lake storage efficiency, and incorporating security measures. * Demonstrated proficiency in PySpark, Python, SQL, and Power BI for tasks involving data processing, visualization, ETL/ELT, and transformation. * Exposure to RAG architectures, vector databases, and agentic AI frameworks for enterprise-scale knowledge and retrieval systems. * Expertise in cloud security guidelines, IAM roles, encryption strategies, and compliance frameworks (GDPR, HIPAA). * Proficiency in CI/CD practices for data solutions using GitHub, GitHub Actions, Terraform, and Azure DevOps or equivalent experience. * Experience implementing real-time and batch data processing solutions using Kafka, Kinesis, Spark Streaming, or Event Hubs. * Strong problem-solving skills with debugging, performance tuning, and AI/ML model deployment in cloud environments., * Effective leadership abilities to build technical choices and steer teams towards data-driven enterprise solutions. * Outstanding interpersonal skills to translate sophisticated technical and AI concepts into business-aligned solutions. * Demonstrable ability to collaborate with team members across IT, business, and AI/analytics departments. * Experience in crafting AI/ML user documentation, solution blueprints, and architecture diagrams. * Passion for continuous learning, innovation, and staying ahead of evolving cloud, AI, and data technologies. ## Description * Build, develop, and implement secure, scalable, and high-performance data solutions using AWS, Microsoft Azure, Databricks, and Microsoft Fabric (Power BI). * Architect end-to-end multi-cloud data platforms, ensuring detailed integration across enterprise data sources, storage, processing, AI services, and consumption layers. * Set up and enforce data governance, security, and compliance protocols within AWS and Azure cloud environments, guaranteeing appropriate access controls and data protection strategies. * Manage the assessment and implementation of cloud-based data structures, such as data lakes, data warehouses, real-time streaming, and advanced analytics. * Collaborate with cross-functional teams, including Data Engineers, Data Scientists, AI/ML Engineers, Security Architects, and Business Analysts, to drive the adoption of modern data and AI architectures. * Maintain guidelines for data modeling, cataloging, lineage tracking, and metadata management across Databricks, Redshift, Synapse, Fabric Lakehouse, and Power BI ecosystems. * Drive innovation in data integration, AI-powered data mesh strategies, agentic AI workflows, and self-service analytics capabilities for enterprise users. ## Related Videos - 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