Senior Data Engineer

Senior Data Engineer – Data Architecture & Platform

CPI Security, a national leader in residential and commercial security solutions, is seeking a Senior Data Engineer transitioning into Data Architecture to join us on our data transformational journey. This unique role combines hands‑on data engineering (70%) with architectural design and governance (30%), ideal for a technical expert ready to shape our enterprise data strategy while remaining deeply involved in implementation.

You’ll work directly with line‑of‑business leaders and technical users to architect and build our cloud data warehouse using Data Vault 2.0 modeling and dbt. This is a technical, hands‑on role, not a pure architecture position, where you’ll mentor junior engineers on a lean team while personally implementing the solutions you design.

This is an on‑site position at our HQ in Charlotte, NC.

This role balances architectural design with hands‑on implementation. You’ll spend approximately 70% of your time coding, building pipelines, and implementing solutions, while dedicating 30% to architectural design, standards definition, and technical guidance. On our lean team, everyone contributes technically, this isn’t about drawing boxes; it’s about designing it AND building it. You must be comfortable in the IDE daily, working alongside engineers and providing mentorship through code reviews, pair programming, and technical guidance.

Define and document reference architectures, design patterns, and standards for the enterprise data platform. Create technical design documentation, data flow diagrams, and architectural decision records (ADRs) while remaining actively involved in hands‑on implementation. Establish data modeling standards, naming conventions, and best practices across the platform.

Establish and maintain data modeling standards, design patterns, and architectural guidelines. Review and approve technical designs to ensure alignment with architectural principles and enterprise standards. Collaborate with stakeholders to define data governance policies and ensure compliance with security requirements.

Provide architectural guidance and hands‑on mentorship to engineers through code reviews, pair programming, and technical design sessions. Share expertise in Data Vault modeling, dbt development, and cloud data engineering best practices. Foster a culture of technical excellence and continuous learning within the team.

Design and implement Data Vault 2.0 modeling patterns to build a scalable, audit‑friendly enterprise data platform that supports business agility and data governance.

Build and maintain automated data pipelines using dbt (Cloud/Core), Python, and Snowflake to transform raw data into business‑ready datasets with comprehensive data quality testing.

Architect and implement an enterprise data platform on Snowflake, including automated deployment pipelines, data quality frameworks, and monitoring solutions. While we modernize to a cloud data platform, on‑premises work is still needed using SSIS and MSSQL Server during the migration phase.

Design and build data marts using dimensional modeling techniques (Kimball methodology) to support business intelligence and analytics requirements.

Design and implement robust data transformation models using dbt, SQL, and Python to build scalable ingestion and processing pipelines.

Implement comprehensive data quality testing frameworks using dbt tests, custom Python validations, and automated monitoring to ensure data accuracy and reliability.

Integrate and operationalize data from external systems such as CRM, ERP, and third‑party platforms via secure cloud data sharing, CDC, and APIs.

Enable reliable, scalable, and automated data workflows by implementing Data Ops best practices for continuous integration, testing, deployment, and…