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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Platform Architect - **Company:** Health Union - **Location:** Philadelphia, PA, United States - **Experience:** Expert - **Salary:** $156,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Computing Platforms, Continuous Delivery, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Dataspaces, High-Level Architecture, Python (Programming Language), Automation of Marketing, Performance Tuning, Query Optimization, Data Streaming, Systems Architecture, Data Ingestion, Large Language Models, Snowflake, Apache Spark, Data Strategy, Data Layers, Core Data, Non-relational Database, Data Management, Data Pipelines - **Published:** June 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0e20739d0ebb2b82 ## About the Role Do you have experience in Technical solutions implementation?, * 8+ years of experience in data engineering or data platform architecture. * 5+ years of hands-on experience designing and evolving unified data platforms built on AWS and Snowflake, with a proven track record of consolidating complex multi-system environments into clean, maintainable architectures. * Experience in healthcare, ad tech, programmatic audiences, or related industries is a plus. * Deep expertise across data ingestion, transformation, data modeling, and pipeline development, including relational and non-relational databases, data streams, file stores, dbt, Apache Airflow, Python, Spark, and advanced SQL. * Strong command of performance tuning, query optimization, and the ability to define and enforce rigorous engineering standards and quality assurance processes across the platform. * Experience implementing CI/CD practices for data pipelines and platform infrastructure. * Understanding of data security, governance, and compliance principles as they apply to platform architecture. * Demonstrated ability to translate data strategy into architectural designs and implementation plans, and lead technical initiatives. * Strong communication and teamwork skills, with the ability to operate effectively across engineering, cross-functional, and leadership audiences, and elevate the engineers around you through mentorship and technical guidance. * A self-motivated, innovative mindset to proactively identify problems, frame solutions, and drive outcomes without waiting to be directed. * Experience with, or active exploration of, how data platform requirements evolve when AI agents and LLMs become data consumers, including implications for warehouse design, semantic layers, and tool interfaces. * Hands-on experimentation with AI and LLM-based tooling in data platform use cases, with a track record of forming and articulating informed opinions in an emerging and fast-moving space. * AWS and Snowflake certifications, such as AWS Certified Data Engineer Associate, AWS Certified Solutions Architect Professional, SnowPro Advanced: Architect, or SnowPro Advanced: Data Engineer, are a strong advantage. ## Description The Senior Data Platform Architect is a highly hands-on, high-impact role centered on execution and technical leadership. You will be the technical leader, translating the technical direction and designs set by our leadership into deployed, highly functional data platforms. Your primary mission is to ensure our vision for enterprise data is realized efficiently and reliably in production. To achieve this, you will design and implement scalable data solutions primarily using AWS and Snowflake, but also incorporating other tools as necessary, given our evolving data ecosystem. You will guide the Data Team and partner across the organization to deliver reliable, high-quality data platforms. This role requires exceptional coordination skills to bridge communication and execution across engineering teams, as well as with critical cross-functional partners. What You Do: * Move fluidly between high-level architecture and hands-on implementation, translating data platform strategy and roadmap into clear, actionable technical designs. * Architect and implement scalable data solutions using AWS and Snowflake, including pipelines, storage layers, and data models, designed from the ground up to serve both human consumers and AI agents. Ensure warehouse design, semantic layer structure, and tool interfaces are ready for LLM and agent-based access patterns as the company's AI capabilities expand. * Design, implement, and evolve a clean, consolidated core data platform architecture across AWS, Snowflake, dbt, and integrated systems by eliminating redundancy and optimizing for performance, cost, and efficiency. * Define authoritative standards for data ingestion, transformation, data modeling, and pipeline development, including ingestion frameworks and tooling, to deliver scalable, resilient, and efficient data movement. * Establish and enforce data quality standards, ensuring freshness, completeness, and reliability through validation, monitoring, and observability. * Solve complex technical challenges with innovation and proactive problem-solving, including cross-system architecture, Snowflake workload optimization, pipeline reliability, and integrating new data sources and applications into the unified platform. * Collaborate across Data, Product, Engineering, and Business teams to deliver aligned, high-impact solutions. * Define and promote best practices for data modeling, pipeline design, and platform architecture. * Ensure systems meet security, governance, and compliance requirements and are production-ready. * Mentor and guide engineers on architecture, design decisions, and engineering best practices, and translate architectural direction into actionable guidance for engineers on complex or high-leverage projects. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Building Multi-Tenant ASP.NET Core Applications: Best Practices and Real-World Solutions](https://www.wearedevelopers.com/videos/1552-building-multi-tenant-asp-net-core-applications-best-practices-and-real-world-solutions) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)