Principal Data Architect and Engineer

**Position Overview:** The Principal Data Architect/Engineer will lead the design, development, and evolution of HomeServe’s metadata-driven AWS Lakehouse platform, combining strategic architecture leadership with hands-on engineering expertise. This role is responsible for delivering scalable, secure, and high-performance data solutions based on Medallion architecture, including Bronze ingestion, PII Vault tokenization, Silver-layer Apache Iceberg (Amazon S3 Tables), and Gold-layer Amazon Redshift data products. The position will drive DataOps automation, governance implementation, and fully ephemeral feature-branch environments to accelerate the delivery of analytics, reporting, and AI/ML capabilities. The ideal candidate will have deep expertise building cloud-native data platforms using Apache Iceberg, Amazon S3 Tables, Lake Formation tag-based access control, DynamoDB single-table design, CloudFormation, and API Gateway with custom authorizers. They will champion Test-Driven Development (TDD), Great Expectations-based data quality validation, and metadata-driven engineering practices to ensure trusted, governed, and reusable data assets that power enterprise analytics, customer 360, AI/ML, and data-driven decision-making across the organization. - Lead the ongoing evolution, optimization, and governance of HomeServe’s AWS-based enterprise Lakehouse platform, ensuring scalability, reliability, security, and operational excellence. - Enhance and support existing metadata-driven ingestion, transformation, and orchestration frameworks, improving performance, maintainability, observability, and developer productivity. - Design, implement, and optimize batch and real-time data processing solutions leveraging AWS Glue, Lambda, Apache Iceberg (Amazon S3 Tables), Redshift, and related cloud-native services. - Manage and continuously improve enterprise data governance and privacy capabilities, including PII tokenization, right-to-erasure workflows, data lineage, and Lake Formation tag-based access controls. - Expand and maintain Customer 360 and Master Data Management (MDM) capabilities, including entity resolution, identity matching, and stewardship processes across enterprise data domains. - Establish and enforce architecture, engineering, and operational standards for a small data engineering team, promoting consistency, quality, and scalability across platform components. - Drive adoption of DataOps and DevOps best practices, including CI/CD automation, Test-Driven Development (TDD), automated data quality validation, and fully ephemeral environments for pull requests and feature branches. - Develop and maintain operational runbooks, monitoring, alerting, and incident response processes, serving as a technical escalation point and incident commander during critical platform events. **Essential Functions:** | **Essential Job Function** | **% of Time on Function** | | --- | --- | | Architecture and design | 25% | | Platform engineering (libraries, IaC, CI/CD) | 25% | | Pipeline build | 20% | | Operations and incident response | 15% | | Stakeholder architecture work and mentoring | 15% | | **Total** | **100%** | **Job Requirements:** - BS in Computer Science or relevant field bachelor’s degree with an advanced degree preferred. - Acts as a forward-deployed senior engineer and technical authority for the data platform who is embedded with business stakeholders, setting standards, leading design reviews, and growing the team. - Deep, recent, hands-on experience as the technical owner of a production AWS Lakehouse. - Development of automated deployment frameworks and CI/CD pipelines to support efficient and reliable data platform releases. - Implementation of comprehensive data validation, monitoring, and quality assurance processes to ensure data accuracy, consistency, completeness, and reliability. - Strong analytical, verbal and written communication and interpersonal skills. - Willingness to travel is required. **Minimum Physica…