> Markdown version of [/jobs/ext/575074-lead-platform-data-engineer](https://www.wearedevelopers.com/jobs/ext/575074-lead-platform-data-engineer). 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 Platform Data Engineer - **Company:** Allegion plc - **Location:** Golden, CO, United States - **Experience:** Expert - **Salary:** $131,400.0 - $205,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Data Security, Interoperability, Python (Programming Language), Machine Learning, NoSQL, Cloud Services, DataOps, Application Data, Software Engineering, SQL Databases, Data Streaming, Technical Data Management Systems, UML, Web Applications, Openapi, Large Language Models, Snowflake, Grafana, Technical Debt, Data Strategy, Cloudformation, Information Technology, Data Lineage, Enterprise Integration, Machine Learning Operations, Terraform, Databricks - **Published:** June 21, 2026 - **Apply:** https://www.juju.com/job/00000000g9qwp5 ## About the Role + **Expert Data Modeling:** Proficiency in designing relational, NoSQL, and **Lakehouse architectures** (e.g., Snowflake, Databricks, or BigQuery). Mastery of SQL is non-negotiable. + **Modern Languages:** Advanced **Python** and/or **Go/Java** for building scalable data applications and custom integrations. + **Orchestration & Transformation:** Expert-level experience with **dbt** and related tools to build repeatable, documented workflows. + **Cloud Infrastructure:** Hands-on experience with **Infrastructure as Code. (Terraform/CloudFormation)** and core cloud services (AWS/Azure/GCP). + **Governance & Quality:** Experience implementing **Data Contracts** , schema registries, and observability tools. What You Need to Succeed: + **Bachelor's Degree** in Computer Science, Data Science, Software Engineering, or a related quantitative field. Master's Degree in a technical field preferred. + **7+ Years in Data Engineering:** With at least **2+ years in a Lead or Staff capacity** , specifically owning the technical roadmap. + **"Ground-to-Cloud" Experience:** A proven track record of entering environments with high technical debt/minimal documentation and successfully implementing a **formal data strategy and topology** . + **Stakeholder Management:** Experience working directly with Product and Executive teams to translate business questions into technical data requirements. + **AI/ML Integration:** Previous experience building feature stores or pipelines specifically designed to feed **AI/ML models or LLMs** . ## Description As a Lead Platform Data Engineer, you will own the data architecture that connects product applications across the full customer lifecycle - from specification and ordering through device provisioning, installation, and ongoing usage. This is a technical leadership role that bridges platform engineering and data engineering: you'll define the entity relationships, data contracts, and semantic models that allow disparate systems to share a common language, while mentoring engineers and driving adoption of data standards across teams. You'll operate with significant autonomy on ambiguous, cross-functional problems - working across organizational boundaries to align teams on shared identifiers, event schemas, and integration patterns. The role requires both architectural vision and the ability to influence stakeholders who don't report to you. _Qualified candidates must be legally authorized to be employed in the United States. The company does not intend to provide sponsorship for employment visa status (e.g., H-1B, TN, etc.) for this employment position._ What You Will Do: Data Architecture & Strategy + **Foundation Building:** Establish and document the organization's first comprehensive **data topology and inventory** , transforming undocumented legacy flows into a structured, scalable platform blueprint. + **Unified Modeling:** Architect cross-application data models and **Data Contracts (OpenAPI/AsyncAPI)** to standardize identity layers and ensure consistency across the product lifecycle. + **AI-Ready Infrastructure:** Design high-performance data flows and transformation layers that surface usage analytics and recurring revenue signals to drive **AI-powered insight generation** . Platform Engineering & Integration + **System Interoperability:** Lead the integration of platform service layers with mobile/web applications to streamline device commissioning and cross-functional data access. + **Modern Orchestration:** Replace ad-hoc processes with robust **workflow orchestration** (e.g., Airflow, dbt) and **CI/CD pipelines** to ensure 99.9% data reliability and "Data-as-Code" standards. + **Strategic Planning:** Drive the technical proposal process, conducting cost-benefit analyses for new systems to balance immediate delivery with long-term platform health. Governance & Engineering Excellence + **Observability & Trust:** Implement automated **data quality monitoring, lineage tracking, and observability** practices to ensure high-fidelity data for downstream analytics and compliance. + **Security & Privacy:** Engineer data lifecycle policies that strictly adhere to global privacy regulations (GDPR/CCPA) and enterprise security standards. + **Technical Mentorship:** Establish and enforce rigorous coding standards and peer review processes, mentoring the team to transition from "plumbing" to modern **DataOps** practices. ## 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) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [ChatGPT and Java: A Match Made in Heaven or Hell?](https://www.wearedevelopers.com/videos/536-chatgpt-and-java-a-match-made-in-heaven-or-hell) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [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) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Got AI ideas but no money? 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