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.

What You'll Do

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.

Data Architecture & Design

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.

Architecture Governance

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.

Technical Mentorship & Collaboration

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.

Data Vault Implementation

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.

Modern Data Engineering

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.

Cloud Data Platform Development

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.

Data Mart & Dimensional Modeling

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

ETL/ELT Pipeline Development

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

Data Quality & Testing

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

External Data Integration

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

DataOps Implementation

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.

Cloud Migration Support

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.

What We're Looking For

Required Experience

• 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

Technical Skills

• 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

Preferred Qualifications

• 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

Soft Skills

• 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

Education

• Bachelor's degree in Information Systems, Computer Science, Data Science, or related field of study preferred
• Work experience equivalent will be considered

What Sets You Apart

• 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

Why Join CPI Security

• Opportunity to architect and build a modern enterprise data platform during an active transformation
• Work with cutting-edge cloud technologies and data vault modeling
• Lead technical design while remaining hands-on with implementation
• Collaborative environment with experienced data professionals on a lean, high-impact team
• Competitive compensation and benefits package
• Professional development opportunities and certification support
• On-site position in Charlotte, NC with a dynamic, growing company

CPI Security is an equal opportunity employer committed to diversity and inclusion in the workplace.

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

About your role

We are looking for a forward-thinking Data Engineering Intern to join our team for Summer 2026. This isn't just a role about moving data from point A to point B; it’s about rethinking how those pipelines are built. You will sit at the intersection of core infrastructure and AI, building robust ETL processes while leveraging AI technologies to automate the very workflows you create.

Your mission is dual-purpose: you will support our Business Intelligence efforts and directly influence our product roadmap by turning raw data into actionable insights through advanced dashboards and automated workflows.

A Day in the Life

• Build & Orchestrate: Design, develop, and maintain ETL pipelines to ingest data into our Snowflake warehouse using Python, SQL, and Airflow.
• AI-Driven Automation: Implement AI-powered solutions to streamline engineering tasks, including:
• Automating code generation and documentation.
• Building AI-driven data quality checks and anomaly detection.
• Developing "self-healing" pipelines that can identify and alert on ingestion errors.
• Insight Generation: Use Jupyter Notebooks and Streamlit to analyze data and build internal tools that help our product team make data-driven decisions.
• Visualization: Create high-impact dashboards in Tableau that translate complex data into a clear narrative for stakeholders.
• Agile Collaboration: Participate in daily Scrum huddles, manage tasks via Jira, and work closely with product owners and QA to promote code to production.
• Cloud Infrastructure: Interact with cloud services via CLI and manage containerized environments using Docker and Kubernetes.

What you’ll need

• Academic Status: Currently pursuing an undergraduate degree with a targeted graduation date in 2026 or early 2027, or pursuing a degree in Computer Science, Data Science, or a related quantitative field.
• Programming Mastery: Expertise in Python and SQL
• Infrastructure Mindset: A strong understanding of Data Warehousing (Snowflake) and ETL orchestration (Airflow).
• DevOps Curiosity: Familiarity with CLI, Docker, and Kubernetes for managing cloud-based environments.
• Analytical Toolkit: Experience with Jupyter Notebooks, Tableau, or Streamlit.
• Problem Solver: A proactive approach to using AI/LLMs to automate repetitive tasks and improve system reliability.

The Summer "Win"

By the end of your 10-week internship, you will have designed and deployed a functional ETL pipeline that feeds into a custom Insights Dashboard. Your work won't just sit in a folder, it will be used to influence our official product roadmap.

Interview Process

• Recruiter Phone Screen
• Technical Assessment 
• Hiring Manager Interview
• Team Interview

ANALYTICS

What We Do

Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic.

What You'll Do

We are seeking a Senior Data Scientist to independently own and drive analytics initiatives for Family Experience (FamXP), Investigation analytics and Trust and Safety, with a focus on impacting team and product outcomes. You'll apply your expertise to transform ambiguous business questions into actionable insights while handling highly sensitive data with care and discretion. This role requires leading cross-functional projects, building strong stakeholder relationships across multiple teams, and maintaining the highest standards of data privacy and security. The role is expected to build foundational re-usable data models as well as end reporting and ad hoc analysis to support teams from FamXP, a product team, to Legal.

In this role, you will

• Own and deliver end-to-end analytics projects for Family Experience and Trust & Safety that drive team outcomes and measurably influence product/org outcomes, from problem framing through impact measurement; can range from telemetry implementation to reporting to automation (from Workato to ML)
• Solve ambiguous Family Experience and Trust & Safety problems by designing analyses, evaluating options/tradeoffs, and making independent decisions that keep work moving in a dynamic environment
• Execute team and product/org strategy through analytics planning: translate strategy into metrics, roadmaps/backlogs, and clear success criteria; contribute to setting team goals
• Build and maintain production-quality metrics, dashboards, and data models that monitor safety, parental controls, and age-appropriate experiences across Epic’s ecosystem
• Drive alignment around approach and outcomes with Trust & Safety, Product, Engineering, Legal, and Policy partners across the team and organization, managing expectations and trade-offs
• Handle sensitive data related to minors and safety incidents with discretion, applying privacy/security best practices and Epic data governance requirements
• Mentor others on the team and within the product/org: share best practices, review work, and raise the bar for how analytics is done

What we're looking for

• 6-10 years of demonstrated ability to own and deliver analytics projects that execute team outcomes and influence product/org outcomes
• Strong SQL skills (Python, PySpark a plus) and experience working with large-scale datasets; comfort in modern data environments (e.g., Snowflake/Databricks/Spark); familiarity with version control and workflow orchestration tools (Airflow or similar) is a plus
• Proven ability to solve ambiguous problems and make independent decisions on team projects with minimal/no oversight
• Experience turning messy data into production-quality metrics, dashboards, and data models that support operational monitoring and decision-making
• Strong judgment handling sensitive or regulated data; working knowledge of privacy/security practices and relevant compliance concepts
• Ability to execute team + product/org strategy via planning and prioritization; can translate goals into measurable outcomes and help set team goals
• Track record of driving alignment and collaboration across immediate/adjacent teams and the broader product/org
• Clear communicator who can align stakeholders through concise updates and documentation that drive decisions and action
• Evidence of mentoring others on the team/product org (coaching, reviews, raising standards)
• Domain strength in Trust & Safety and/or family experiences online (e.g., moderation, account safety, community health, fraud, or safety feature measurement)

EPIC JOB + EPIC BENEFITS = EPIC LIFE

Our intent is to cover all things that are medically necessary and improve the quality of life. We pay 100% of the premiums for both you and your dependents. Our coverage includes Medical, Dental, a Vision HRA, Long Term Disability, Life Insurance & a 401k with competitive match. We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents. Throughout the year we celebrate our employees with events and company-wide paid breaks. We offer unlimited PTO and sick time and recognize individuals for 7 years of employment with a paid sabbatical.

ANALYTICS

What We Do

Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic.

What You'll Do

Epic Games is looking for a hands-on Data Science Lead to join the Gameplay Analytics team. You’ll lead a team of Data Scientists and Data Engineers and apply mixed methods to own the end-to-end life cycle of creating data assets, reports, insights, to impact the direction of efforts across Epic’s portfolio of products and ecosystems, with a particular focus on our Shooters Games (Battle Royale, Reload, OG, Blitz). The successful candidate will have the ability to apply a range of data technologies, statistical methods, and visualization methods to influence development and product teams, to manage a small team, and to partner with stakeholders across all parts of the business.

In this role, you will

• Partner with design, game development, and product management counterparts to identify opportunities for our first party Games and the business, and use data to develop metrics and insights that shape the execution of the strategy
• Work directly with engineering and data platform teams to properly scope and capture the data required to unlock insights and data models
• Transform raw data into data models, production metrics, reports, and insights
• Continuously evaluate the effectiveness of metrics and align them with long-term ecosystem growth
• Work with design, product, and analytics teams to quickly and rigorously design, test, and learn from experiments to improve our games
• Lead a small team of data analysts, help mentor them, and set the direction of our analytics approach

What we're looking for

• At least 5 years of industry or relevant experience, with proven interest in and knowledge of live service video games
• At least 2 years of experience managing a team of data professionals
• Strong product intuition and demonstrated background in influencing products by applying data and measurement to drive alignment
• Experience with working with development teams to instrument data and ensure continued data quality
• Experience with writing efficient and scalable SQL over billions of rows; it is a plus if you are familiar with distributed computing using Spark (Scala or PySpark)
• Development experience in Python analytics ecosystem
• Familiarity with supporting operational processes including: Code version control (Github or similar), Orchestration (Airflow), AI coding tools (Claude Code)
• Understanding of experimental design and A/B testing techniques
• Advanced statistical training and a thorough understanding of the associated strengths and weaknesses of different statistical approaches is a plus
• Experience in a “full-stack” environment - data file ingest, ETL, data storage interaction, application development, communication of results to storage systems, code version control is a plus

EPIC JOB + EPIC BENEFITS = EPIC LIFE

Our intent is to cover all things that are medically necessary and improve the quality of life. We pay 100% of the premiums for both you and your dependents. Our coverage includes Medical, Dental, a Vision HRA, Long Term Disability, Life Insurance & a 401k with competitive match. We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents. Throughout the year we celebrate our employees with events and company-wide paid breaks. We offer unlimited PTO and sick time and recognize individuals for 7 years of employment with a paid sabbatical.