Data Engineer - Data & AI Applications

This is a remote position.

CPI is seeking a Data Engineer to join our growing team! We are a full-service consultancy and professional services firm specializing in large capital projects (infrastructure, energy, etc). We are headquartered in Los Angeles, CA, but our team is fully remote.

Job Summary: The Data Engineer plays a key role in supporting analytics, reporting, data workflows, and AI-enabled application development. This role requires strong technical problem-solving, hands-on experience with SQL and Python, the ability to support business-facing reporting and visualization needs, and the capability to help build practical AI-enabled tools, prototypes, automations, and data applications. The ideal candidate is a versatile technical contributor who can work across data engineering, analytics, and application development while collaborating with technical leads, stakeholders, and cross-functional teams to deliver reliable, well-documented solutions.

Key Responsibilities

• Build and maintain data workflows, pipelines, automations, and application components that support analytics, reporting, and AI enabled use cases.

• Support the development of AI enabled tools, prototypes, and applications by preparing data, integrating APIs or AI services, and implementing reusable technical components.

• Collaborate with stakeholders and the Technical Lead to understand data, reporting, application, and AI workflow requirements and translate them into practical technical solutions.

• Design, monitor, and optimize ETL processes, data workflows, and automation scripts for reliability, accuracy, and maintainability.

• Develop and enforce data validation, lineage, quality checks, and documentation across reporting, analytics, and AI application workflows.

• Ensure data is organized, clean, secure, and accessible for analytics, reporting, dashboarding, and application use cases.

• Build, maintain, or support Power BI data models, dashboards, reports, and other business facing data products as needed.

• Create and maintain documentation of pipeline logic, data flow, code, prompts, assumptions, dependencies, and technical decisions.

• Support lightweight user facing tools, prototypes, interfaces, or interactive outputs that help users consume data and AI generated results effectively.

• Work with the Technical Lead to scope assigned work, clarify requirements, identify risks, and align technical decisions with broader project and system priorities.

• Use version control, automation, reusable code patterns, and development best practices to support maintainable delivery.

• Communicate progress, blockers, technical findings, and tradeoffs clearly to team members, stakeholders, and project leadership.

• Proactively identify opportunities to improve reporting processes, data workflows, AI application components, documentation, and delivery efficiency.

• Support data integrity, security, quality, and governance expectations throughout analytics, reporting, and application development work.

• Accurate and timely timekeeping.

Performance Metrics

• Delivers reliable, accurate, and maintainable data workflows, reporting assets, automations, and AI application components on time.

• Supports organization wide projects, client engagements, and internal initiatives across analytics, reporting, data engineering, and AI enabled application development.

• Owns assigned technical workstreams, including requirements clarification, build execution, validation, documentation, stakeholder communication, and handoff.

• Demonstrates practical technical judgment when developing scalable, reusable, and maintainable solutions.

• Maintains clear documentation and reusability of pipelines, scripts, reports, prompts, application components, data flows, and technical decisions.

• Builds and supports data systems, dashboards, reports, and application workflows that are reliable, performant, and useful for business stakeholders.

• Produces clear, accurate, and business consumable reporting outputs, data visualizations, technical findings, and AI enabled deliverables.

• Communicates progress, blockers, risks, assumptions, and technical tradeoffs clearly and proactively.

• Identifies and communicates process improvement opportunities across reporting, data workflows, automation, documentation, and AI application delivery.

• Supports data integrity, security, validation, automation, documentation, and version control best practices.

• Is recognized as a dependable technical owner for assigned systems, workflows, tools, reports, or application components.

• Demonstrates growth toward broader ownership of data and AI enabled solution delivery.

Requirements

Required Skills and Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Business Analytics, Engineering, or a related field, or equivalent work experience.

• 5+ years of relevant technical experience across data engineering, data analysis, analytics engineering, application development, automation, business intelligence, or related technical work.

• Proficiency in SQL and Python for data processing, automation, analysis, and application support.

• Experience building or maintaining data pipelines, ETL processes, data workflows, automation scripts, dashboards, reports, or internal tools.

• Experience preparing, cleaning, validating, transforming, and documenting data for analytics, reporting, and application use cases.

• Experience supporting downstream analytics and reporting needs, including Power BI dashboards, reports, data models, or similar business intelligence products.

• Familiarity with AI enabled tools, generative AI workflows, LLM based applications, prompt workflows, AI assisted automation, or API based AI service integration.

• Experience integrating APIs, databases, files, external services, or structured and semi structured data sources into technical workflows.

• Understanding of database management, data modeling, data quality, data validation, and data integrity best practices.

• Demonstrated use of version control, documentation standards, reusable code practices, and process automation.

• Ability to own assigned technical workstreams with minimal oversight, including requirements clarification, build execution, validation, documentation, and handoff.

• Ability to communicate technical information, data findings, limitations, risks, and recommendations clearly in writing and verbally.

• Strong analytical thinking, problem solving skills, attention to detail, and continuous improvement mindset.

• Experience collaborating effectively with Technical Leads, analysts, developers, stakeholders, and cross functional or matrixed teams.

Preferred Skills and Qualifications

• Exposure to front end or user interface technologies such as HTML, JavaScript, AngularJS, jQuery, or similar technologies.

• Experience with tools such as Airflow, dbt, or similar orchestration and transformation frameworks.

• AWS, Azure, Microsoft Fabric, or other cloud data platforms (e.g., Snowflake, Databricks) a plus.

• AWS Cloud Practitioner, AWS Solutions Architect, or equivalent certification.

• Generative AI (GenAI) and machine learning (ML), including retrieval augmented generation, embeddings, vector databases, structured outputs, tool calling, agents, or evaluation workflows.

• Energy utility domain knowledge.

Benefits

• Salary: $120,000-$135,000+ depending upon qualifications and experience.

• Work from home (fully remote)

• 2 weeks paid time off

• Home equipment allowance (monitors, stand-up desk, etc.)

• Annual education allowance

• 401(k) with company matching

• Medical, Dental, Vision, and Life insurance