Tech Stack:SQL, dbt, Snowflake, Fivetran, Python, Power BI, and cloud-native/DevOps tooling, with growing use of AI-assisted development tools.

Principal Responsibilities:

Data Pipeline Development & Platform Engineering

• Design, build,  and optimize scalable data pipelines and ETL/ELT processes using dbt, Snowflake, Fivetran, and other modern data stack tooling

• Improve reliability, observability, and performance across the data engineering environment

• Troubleshoot and resolve pipeline failures, transformation issues, and performance across the data engineering environment

Data Modeling & Analytics Engineering

• Develop and maintain data models supporting operational reporting, executive analytics, financial analysis, and AI-driven initiatives

• Design curated datasets and transformation layers aligned with analytics engineering best practices

• Ensure data structures are consistent, usable, and maintainable for downstream business intelligence needs

• Contribute to semantic-layer-aligned reporting structures and reusable enterprise datasets

Data Quality, Governance & Reliability

• Implement data quality validation, testing standards, and monitoring workflows

• Investigate and resolve data discrepancies and reporting reliability concerns

• Support enterprise data governance standards and documentation practices

Reporting, Business Partnership & Collaboration

• Partner with stakeholders to translate business needs into scalable data solutions

• Prepare and optimize datasets supporting dashboards, KPIs, and operational reporting

• Participate in architecture discussions, data design reviews, and technical planning

• Serve as a technical resource for enterprise reporting and analytics needs

AI-Enabled Data Workflows & Team Growth

• Leverage AI-assisted tools to improve SQL development, transformation efficiency, and engineering productivity

• Support preparation and validation of datasets used in AI/ML initiatives

• Provide guidance and technical mentorship to junior data engineers, promoting knowledge sharing and operational ownership

Education and Certifications:

• Required: Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field

Required Experience:

• 5–7 years of experience in data engineering, analytics engineering, business intelligence, or related technical roles

• Strong hands-on experience building and maintaining ETL/ELT pipelines and modern data workflows

• Advanced SQL proficiency and experience with dbt or similar transformation frameworks

• Experience working with Snowflake or similar cloud-native data platforms

• Strong understanding of data modeling, analytics engineering, and enterprise reporting concepts

• Experience troubleshooting data quality, transformation, and operational reliability issues

• Experience working with cross-functional business and technical stakeholders

• Strong analytical, technical problem-solving, and organizational skills

Preferred Experience:

• Experience with Power BI, semantic layer tooling, or enterprise reporting platforms

• Familiarity with Python or scripting languages supporting automation and data workflows

• Exposure to AI-assisted engineering workflows and intelligent automation tooling

• Experience supporting AI use cases or operational analytics environments

• Experience with cloud-native tooling, observability practices, or DevOps workflows

• Experience in healthcare staffing, workforce solutions, or service-based organizations preferred

Location:

• This role is hybrid for candidates located within a reasonable commuting distance to our Edmond, OK or Frisco, TX offices. Candidates outside a reasonable distance from either office are eligible for a fully remote arrangement.

Compensation:

• The expected base salary range for this position is $140,000 to $155,000 annually. The final compensation offered will be determined based on a number of factors, including but not limited to skills, qualifications, experience, and location.