Senior Data Engineer
About The Position
This role reports to the Senior Data Engineer Manager and operates within a small, focused Data Engineering team. The Senior Data Engineer is responsible for designing, developing, optimizing, and maintaining scalable data pipelines, transformation workflows, and data models that support enterprise reporting, analytics, operational intelligence, and AI-enabled initiatives across the organization. This role operates as a fully independent technical contributor with increasing ownership over SaaS data engineering initiatives, platform reliability, and analytics engineering workflows. The Senior Data Engineer contributes directly to the organization’s modern data platform while partnering closely with Data & Analytics leadership, Engineering, AI & Machine Learning, Product managers, Operations, Finance teams, and clients to ensure data solutions are scalable, accurate, reliable, and aligned with business priorities. The Senior Data Engineer is expected to contribute to architecture discussions, optimize data workflows, improve reporting scalability, and support modern analytics engineering practices while mentoring junior engineers and helping improve operational maturity within the data environment. Tech Stack: SQL, dbt, Snowflake, Fivetran, Python, Power BI, and cloud-native/DevOps tooling, with growing use of AI-assisted development tools.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field
- 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
Nice To Haves
- 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
Responsibilities
- 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
- 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
- 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
- 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
- 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
Benefits
- The expected base salary range for this position is $ 140,000 to $ 155,000 annually.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
