Data & AI Engineer

Ledgent Technology; Sacramento (CA); On-site; USD 130,000 - 190,000; Full time

Job summary

Ledgent Technology is seeking a Data & AI Engineer to design, develop, and maintain data pipelines powering enterprise data integration and analytics. You will partner with data scientists, analysts, and AI engineers to ensure data quality, governance, and scalable delivery across the data platform.

The role emphasizes applying AI foundations, building reliable ETL/ELT processes, and collaboration across teams to drive AI-enabled data capabilities for the organization.

Qualifications

• Proficient in designing, building, and maintaining scalable data pipelines and ETL/ELT processes.
• Experience with cloud data platforms and services (Azure, Databricks) and modern data warehousing concepts.
• Strong programming skills in Python and SQL; knowledge of additional languages is a plus.
• Hands-on with AI and foundation models, retrieval-augmented generation, and agent-building skills.

Responsibilities

• Designs and develops data pipelines that extract, transform, and load data into the data platform.
• Integrates data from databases, data warehouses, APIs, and external systems with data quality validations.
• Applies AI capabilities to support business use cases and data platform features.
• Partners with data scientists and analysts to optimize models for data quality and governance.
• Implements data quality checks and drives data governance practices across the organization.
• Collaborates across teams to ensure timely delivery and adoption of data products.

Skills

Python

SQL

APIs

ETL/ELT

MLOps/AIOps

AI/LLMs

Data governance

Data quality

Agile

Cross-team collaboration

Tools

Azure

Databricks

Power BI

Tableau

GitHub

Azure DevOps

Job description

This position is responsible for designing, developing, and maintaining the data pipelines, infrastructure, and systems that enable reliable data integration, transformation, and delivery across enterprise data platform.

The Data & AI Engineer partners with data scientists, analysts, and AI engineers to ensure data is high-quality, well-governed, and ready to support analytics, AI, and business intelligence, and applies foundational AI and agent-building skills to deliver solutions to business problems.

This role sits within the Data & Technology Solutions department and contributes to the build-out of enterprise data platform and AI capabilities.

Responsibilities

Essential duties and responsibilities, i.e. those which are basic, necessary, and an integral part of the job, are indicated below:

• Designs and develops data pipelines that extract data from various sources, transforms it into the desired format, and loads it into data platform.
• Integrates data from databases, data warehouses, APIs, and external systems, including telematics, work order, and other operational systems; ensures data consistency and integrity during integration, performing validation and cleaning as needed; develops and maintains APIs as needed to enable data exchange between systems.
• Applies foundational AI and agent-building skills, such as working with large language models, basic tool use, and retrieval-augmented generation, to support business use cases that require AI and data platform features.
• Serves as a visible ambassador for data and AI across the organization.
• Implements data quality checks and validations within pipelines to ensure accuracy, consistency, and completeness; partners with leadership on data governance practices.
• Optimizes data pipelines and processing workflows for performance, scalability, and efficiency; monitors and tunes data systems and identifies and resolves performance bottlenecks.
• Collaborates with data scientists and analysts to optimize models and algorithms for data quality, security, and governance; supports delivery and educates end users on data products.

Specific Job Requirements

• Successful completion of pre-employment drug, alcohol, and background investigation.
• Ability to build trust and rapport quickly with employees at all levels, demystifying data and AI for non-technical audiences, and championing responsible adoption through day-to-day partnership.
• Demonstrated expertise in designing, building, and maintaining scalable data pipelines and ETL/ELT processes.
• Proficiency with cloud data platforms and services such as Azure and Databricks; experience with modern data warehousing and data architecture concepts.
• Strong programming skills in Python and SQL; working knowledge of additional languages (e.g., Java, R) is a plus.
• Hands-on experience applying AI and building foundational AI agents (e.g., using large language models, basic tool use, or retrieval-augmented generation) to real use cases required.
• Experience with MLOps/AIOps practices for deploying, monitoring, and maintaining models and data/AI pipelines in production preferred.
• Experience with version control tools (e.g., GitHub, Azure DevOps), Agile software development best practices, AI-assisted coding tools (e.g., Claude Code) to accelerate development; and data visualization platforms (e.g., Power BI, Tableau) preferred.
• Ability to collaborate across teams of varying technical backgrounds to support delivery.
• Strong problem-solving and debugging skills, including the ability to diagnose issues in unfamiliar code or systems.
• Ability to translate between technical, business, and executive stakeholders on data sources, data management concepts, and analytical approaches.
• Ability to preserve confidential and proprietary information and successfully avoid conflicts of interest.
• Must be able to prioritize, manage multiple workstreams, and recognize when to seek direction.

All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, Los Angeles County Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.