Principal Responsibilities:

Data Pipeline Development & Optimization

• Design, build, maintain, and optimize scalable data pipelines supporting enterprise analytics, reporting, and operational workflows

• Develop and enhance ETL/ELT processes using modern data stack technologies such as dbt, Snowflake, Fivetran, and cloud-native tooling

• Improve reliability, scalability, observability, and operational performance of enterprise data workflows

• Troubleshoot and resolve complex pipeline failures, transformation issues, and data delivery bottlenecks

Data Modeling & Analytics Engineering

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

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

• Ensure data structures support consistency, usability, maintainability, and downstream business intelligence requirements

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

Data Quality, Governance & Reliability

• Implement and improve data quality validation processes, testing standards, and operational monitoring workflows

• Investigate and resolve data discrepancies, transformation inconsistencies, and reporting reliability concerns

• Support enterprise data governance standards, documentation practices, and operational data integrity initiatives

• Promote operational consistency and scalable data engineering standards across the organization

Reporting, Analytics & Business Enablement

• Partner with stakeholders to support SaaS product reporting, analytics, and operational intelligence initiatives

• Prepare and optimize datasets supporting dashboards, KPIs, operational reporting, and business intelligence workflows

• Collaborate with Product managers, Finance, Operations, and Technology teams to translate business requirements into scalable data solutions

• Improve accessibility and usability of enterprise data assets across reporting and analytics environments

AI-Enabled Data Workflows & Automation

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

• Support preparation and optimization of datasets used in AI and machine learning initiatives

• Validate AI-assisted outputs related to data engineering workflows, reporting logic, and transformation processes

• Identify opportunities to improve scalability and operational efficiency through automation and reusable engineering practices

Platform Optimization & Engineering Best Practices

• Contribute to optimization of Snowflake, dbt, reporting pipelines, and enterprise data platform workflows

• Improve engineering standards related to testing, deployment, monitoring, observability, and documentation

• Support modernization initiatives focused on scalability, reliability, and operational efficiency improvements

• Promote consistent engineering workflows and modern data engineering practices across the organization

Cross-Functional Collaboration & Technical Partnership

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

• Support integration of enterprise operational systems and downstream reporting environments

• Serve as a technical resource supporting SaaS product reporting and analytics needs

Mentorship & Technical Development

• Provide guidance and technical support to junior Data Engineers and analytics resources

• Promote knowledge sharing, operational ownership, and continuous technical improvement across the team

• Contribute to the organization’s long-term data engineering maturity and operational scalability

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.