Senior Data Engineer

CPI Security•Charlotte, NC

22h•Onsite

About The Position

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.

Requirements

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)
Proven experience with automated deployment and CI/CD pipelines
Experience implementing data quality testing frameworks
Experience designing data architectures and creating technical documentation (data models, architecture diagrams, design patterns, ADRs)
Proven ability to balance architectural thinking with hands-on implementation
Experience mentoring and guiding junior/mid-level engineers through technical collaboration
MSSQL Server SQL and SSIS
Advanced SQL and data modeling expertise with dimensional modeling and data vault modeling
Strong dbt skills for data staging, cleaning, transformation, testing, and modeling
Proficiency in Python programming for data engineering tasks
Experience with agile/scrum teams for data engineering and analytics engineering
AWS cloud services (S3, Lambda, IAM, CloudFormation, etc.)
Experience with data orchestration tools (Airflow, Prefect, or similar)
Understanding of modern data engineering practices and agile methodologies
Knowledge of data governance, security, and compliance requirements
Excellent oral and written communication skills to effectively deliver messages to a wide range of audiences, from business to technical
Innovative and positive team member mindset
Strong teamwork and interpersonal skills, with the ability to deliver results working independently or in a collaborative environment
Agile development experience preferred
Solution-oriented approach with strong problem-solving abilities
Deep understanding of the complete data engineering lifecycle
Architectural design experience combined with strong implementation skills
Experience with cloud data platform implementations and migrations
Proven ability to work with cross-functional teams and stakeholders
Passion for building modern, cloud-first data solutions
Strong analytical and critical thinking skills
Commitment to data quality and best practices

Nice To Haves

AWS Certified Developer certification
Snowflake certifications in data engineering and/or architecture
Experience with data vault automation tools (automate-dv package)
Knowledge of modern BI and analytics platforms

Responsibilities

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.
Work collaboratively on our small team where everyone contributes to solving complex technical challenges.
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.
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 DataOps 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.