Lead Platform Data Engineer

Creating Peace of Mind by Pioneering Safety and Security Role Summary 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. 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. Technical Skills 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 . What You'll Get from Us Health, dental and vision insurance coverage, helping you “be safe, be healthy”. A commitment to your future with a 401K plan, offering a 6% company match and no vesting period Tuition Reimbursement Unlimited PTO Employee Discounts through Community involvement and opportunities to give back so you can “serve others, not yourself”. Opportunities to leverage your unique strengths through CliftonStrengths testing and coaching Compensation This range is provided by Allegion. Your actual pay will be based on your skills and experience. The expected Base Salary Range: $131,400 - $205,000. The actual compensation will be determined based on experience and other factors permitted by law. Bonus Eligible: Yes #J-18808-Ljbffr Schlage Lock CO