> Markdown version of [/jobs/ext/3039314-lead-data-architect](https://www.wearedevelopers.com/jobs/ext/3039314-lead-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Architect - **Company:** Dynatrace LLC - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $160,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Third Normal Form, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Warehousing, Software Design Patterns, Dimensional Modeling, Microsoft Software, Operational Data Store, Open Source Technology, Performance Tuning, Raw Data, Role-Based Access Control, Power BI, Search Technologies, Tableau (Software), Management of Software Versions, Enterprise Data Management, Google Cloud, Large Language Models, Snowflake, Data Lakes, Infrastructure Automation Frameworks, Graphql, Operational Systems, Api Design, Dynatrace, Databricks - **Published:** September 23, 2026 - **Apply:** https://www.builtincolorado.com/job/lead-data-architect/11312366?handler=ApplyRedirect ## About the Role * 8+ years in data engineering, analytics engineering, or data architecture, with at least 3 years in an architecture or technical leadership capacity * Deep hands-on experience with Snowflake - dynamic tables, RBAC/RLS, column masking, performance optimization * Proven experience designing Medallion Architecture at enterprise scale * Strong command of both 3NF and Dimensional Modeling in production environments * Experience architecting a semantic layer - dbt Semantic Layer, Tableau / PowerBI, or equivalent * Hands-on experience with Etl/ELT methods, dbt and the patterns that make pipelines maintainable, testable, and observable * Track record of driving dataset adoption in partnership with business and BI stakeholders Desirable * Experience with Databricks, Delta Lake, or Snowflake Unity Catalog * Exposure to LLM integration patterns - RAG, semantic search, structured data grounding, agentic data access * Experience with data API design - REST or GraphQL over warehouse data, contract management, versioning * Familiarity with domain-oriented data ownership models and what makes them succeed organizationally * Working knowledge of cloud infrastructure (AWS, Azure, or GCP) and infrastructure-as-code practices * Contributions to open-source tooling or published architectural thinking ## Description Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred. The summary above was generated by AI Your role at Dynatrace As a Lead Data Architect you will provide hands-on technical leadership role defining how data is modeled, structured, and consumed across our enterprise data platform. You will own the architectural standards that turn raw data into trusted, reusable, and AI-ready assets across our data warehouse, data lake, and the downstream applications and models that depend on them. This is a remote eligible position. Candidates who live within a 45 mile radius of Boston, MA; Detroit, MI; and Denver, CO will be required to work hybrid (2 days per week) out of our Dyntrace office. Candidates are required to work EST hours for this position. Key Responsibilies * Design enterprise data models across core business domains using 3rd Normal Form and Dimensional Modeling knowing when each is the right tool and being able to defend the tradeoff * Define and enforce the Medallion Architecture layering strategy - what belongs in Bronze, Silver, and Gold, when curation adds value vs. overhead, and how raw data can be responsibly exposed to downstream consumers * Set guardrails for ELT pipeline architecture: source alignment, incremental load strategies, and failure handling expectations * Architect and build the semantic layer for LLM-powered applications - ontology design, entity resolution, metadata enrichment, and how structured datasets are surfaced to AI agents and RAG pipelines * Define interface standards between the data platform and analytics/application workloads - API source design patterns, latency SLAs, and the boundary between warehouse and operational data store. * Design RBAC and RLS implementations that reflect how the business organizes around data, without making access a bottleneck * Partner with business and BI teams to connect Snowflake data models to BI tool implementations, drive dataset adoption, and translate business questions into reusable modeled assets * Author modeling standards, and platform guidelines; conduct architecture reviews; and mentor data and analytics engineers ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)