Senior Data Engineer

Charlotte, North Carolina, United States

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.

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 are modernizing 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 monitoring across the data pipeline lifecycle. Establish and maintain Snowflake security governance through role‑based access control (RBAC), including the design and management of role hierarchies, privilege grants, and object‑level permissions to enforce least‑privilege principles across all data assets. Define and enforce data access policies for users, service accounts, and downstream consumers by leveraging Snowflake's virtual warehouses, resource monitors, row‑level security, and dynamic data masking to ensure compliant and auditable data access at scale.

Play an integral role in planning, designing, and implementing data migration strategies from legacy on‑premises SQL Server systems to our modern Snowflake cloud platform.

• 6+ years of data engineering experience with cloud data platforms
• 4+ years of experience with Snowflake (required)
• 4+ years of experience with dbt (Cloud and/or Core)
• 4+ years of Python development experience
• 4+ years of AWS experience (AWS Certified Developer preferred)
• 6+ years of experience building data warehouses and data marts
• Experience using Data Vault 2.0 modeling methodology
• Strong experience with dimensional modeling (Kimball methodology)
• Prove…