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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** HMG America - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Warehousing, Digital Assets, Meta-Data Management, Cloud Platform System, Data Strategy, Data Layers, Data Lakes, Pyspark, Data Lineage, Data Management, Databricks - **Published:** August 21, 2026 - **Apply:** https://www.dice.com/job-detail/1123f753-c37e-48fb-9fc2-de91f80dc74f ## About the Role * Extensive experience with the Databricks ecosystem, including: + Databricks Lakehouse + Delta Lake + Unity Catalog + Delta Live Tables (DLT) + Databricks SQL + PySpark * Strong expertise in: + Enterprise Data Architecture + Data Modeling and Data Warehousing + Semantic Layer Design + Data Platform Modernization * Proven experience designing and implementing Medallion Architecture (Bronze, Silver, Gold) patterns. * Strong understanding of: + Data Governance + Data Lineage + Metadata Management + Data Quality Frameworks + Security and Access Controls * Demonstrated ability to lead large-scale enterprise data transformation programs., * 12+ years of experience in Data Engineering, Data Architecture, Data Platform Modernization, or related disciplines. * Proven track record leading enterprise-scale Databricks Lakehouse implementations. * Experience designing Supply Chain Management (SCM) data models and semantic consumption layers. * Strong consulting and client-facing experience with the ability to influence senior stakeholders. * Excellent leadership, communication, and problem-solving skills. * Experience managing globally distributed teams and complex technology programs. ## Description Seeking a Senior Data Engineering Lead to spearhead a strategic Data Foundation and Platform Modernization initiative. This leadership role will be responsible for designing and implementing a modern Databricks Lakehouse Platform, establishing enterprise-wide data standards, and defining a Unified Data Model (UDM) for the Supply Chain Management (SCM) domain., * Lead the design and implementation of a modern enterprise data platform leveraging the Databricks Lakehouse architecture. * Drive migration and modernization initiatives from legacy platforms to cloud-native data ecosystems. * Define best practices for scalability, performance, reliability, security, and cost optimization. Unified Data Model Architecture * Design and govern a comprehensive Supply Chain Management (SCM) Unified Data Model spanning source systems, ingestion, transformation, semantic, and consumption layers. * Establish enterprise standards across Bronze, Silver, Gold, and Semantic layers following Medallion Architecture principles. * Ensure alignment of business definitions, metrics, and reporting standards across the organization. Data Governance & Quality * Implement robust data governance frameworks covering metadata management, lineage, security, and compliance. * Define and enforce enterprise data quality standards, validation processes, and monitoring mechanisms. * Promote reusability of data assets and enterprise-wide data stewardship practices. Leadership & Delivery Management * Lead and mentor high-performing onsite and offshore engineering teams. * Drive architectural decisions, technical standards, and delivery excellence across multiple workstreams. * Foster a culture of innovation, collaboration, and continuous improvement. Stakeholder Collaboration * Partner with business leaders, product owners, and technical stakeholders to understand strategic priorities and translate them into scalable data solutions. * Serve as a trusted advisor for data strategy, platform transformation, and analytics enablement initiatives. * Communicate architectural vision, progress, risks, and recommendations to executive stakeholders. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [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) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [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) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)