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Experity, Inc.

Staff Data Engineer - Full Time

United States

Compensation: Budgeted between $140,750 and $190,000 dependent upon applicable experience. · Full-time

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Job details

Pay: Compensation: Budgeted between $140,750 and $190,000 dependent upon applicable experience.
Job type: Full-time
Experience: 8+ years of experience building and operating production-grade data platforms, including demonstrated ownership of complex systems or cross-team technical initiatives.
Posting language: English
Posted: Nov 3, 2026

Original job description

Experity is a mission-driven team transforming on-demand healthcare across the U.S., empowering urgent care clinics with industry-leading software that makes care faster, easier, and more patient-focused. Joining us means doing meaningful work that directly improves the healthcare experience for millions - from helping families access care quickly to ensuring clinics run smoothly behind the scenes. If you want to make a real impact alongside innovative, dedicated teammates while contributing to a trusted platform that’s becoming the operating system for on-demand care, Experity is the place to grow your career.

Experity offers the following:

Benefits – Comprehensive coverage starts first day of employment and includes Medical, Dental/Orthodontia, and Vision.
Ownership - All Team Members are eligible for synthetic ownership in Experity upon one year of employment with real financial rewards when the company is successful!
Employee Assistance Program - This robust program includes counseling, legal resolution, financial education, pet adoption assistance, identity theft and fraud resolution, and so much more.
Flexibility – Experity is committed to helping team members face the demands of juggling work, family and life-related issues by offering flexible work scheduling to manage your work-life balance.
Paid Time Off (PTO) - Experity offers a generous PTO plan and increases with milestones to ensure our Team Members have time to recharge, relax, and spend time with loved ones.
Career Development – Experity maintains a learning program foundation for the company that allows Team Members to explore their potential and achieve their career goals.
Team Building – We bring our Team Members together when we can to strengthen the team, build relationships, and have fun! We even have a family company picnic and a holiday party.
Total Compensation - Competitive pay, quarterly bonuses and a 401(k) retirement plan with an employer match to help you save for your future and ensure that you can retire with financial security.

Compensation: Budgeted between $140,750 and $190,000 dependent upon applicable experience.

Remote: Experity offers Team Members the opportunity to work remotely or in an office.

Responsibilities:

Data Engineering & Platform

Lead the architecture and hands-on delivery of scalable batch and near-real-time ETL/ELT pipelines and data platform services.
Define robust integration patterns for databases, APIs, applications, CDC/event streams, and external sources across Experity's enterprise data platform.
Design reusable, governed data models, curated data products, and semantic-ready datasets for analytics, reporting, AI/ML, and operational applications.
Solve complex transformation and processing challenges using Python, SQL, Snowflake, and distributed data technologies; contribute production-quality code.
Drive architectural decisions and tradeoffs for scalability, availability, resiliency, performance, maintainability, and cost efficiency.

Engineering Excellence & DataOps

Define reusable frameworks, libraries, reference architectures, and engineering patterns adopted across data engineering teams.
Advance automated testing, CI/CD, Infrastructure as Code, and DataOps standards; improve developer workflows using AI-assisted engineering tools with appropriate review and controls.
Establish observability, data freshness, service-level objectives, alerting, and automated recovery patterns for critical data pipelines.
Lead resolution of high-impact production issues, cross-system root-cause analysis, and preventive architectural improvements.
Drive measurable improvements in Snowflake and cloud compute efficiency, query performance, storage, and platform operating costs.

Data Quality, Governance & Security

Set technical standards for data quality, validation, lineage, reconciliation, and trusted data delivery across critical domains.
Partner with Data Architecture, Governance, and Security teams to design discoverable, governed, reusable data assets and consistent access patterns.
Design healthcare data solutions with privacy, security, and applicable compliance requirements embedded from the outset.

Technical Leadership & Collaboration

Serve as a technical authority for cross-team design reviews, architecture decisions, code quality, and engineering best practices.
Mentor Senior and other Data Engineers through design guidance, pairing, code reviews, and technical knowledge sharing; lead through influence rather than direct reports.
Partner with Data Scientists and Machine Learning Engineers on reliable feature
pipelines, ML-ready datasets, and governed data access for Generative AI and agentic applications.
Translate ambiguous product and business needs into practical architecture, phased
delivery plans, and measurable technical outcomes.
Communicate architectural decisions, tradeoffs, risks, and operational practices clearly to engineering and non-engineering stakeholders.

Education and Experience:

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
8+ years of experience building and operating production-grade data platforms, including demonstrated ownership of complex systems or cross-team technical initiatives.
Expert proficiency in Python and SQL, with strong software design, testing, debugging,and code review practices.
Deep hands-on experience with Snowflake, including data modeling, query optimization, performance, and cost management.
Experience architecting CDC, Kafka, Flink, or comparable distributed event and streaming solutions.
Strong experience with AWS, including S3, Lambda, Glue, Kinesis, or equivalent cloud services.
Proven experience designing high-volume batch and near-real-time ETL/ELT architectures and reusable analytical data models.
Experience with orchestration technologies such as Airflow or equivalent platforms.
Experience establishing CI/CD, Git-based workflows, automated testing, and Infrastructure as Code practices.
Strong command of data quality, governance, security, observability, production operations, and reliability engineering.
Demonstrated ability to lead technical decisions across teams, mentor engineers, and communicate tradeoffs effectively.
A hands-on, full-stack mindset and willingness to own complex problems end-to-end, from design through production operations.

Preferred:

Experience with dbt and dimensional modeling or semantic-layer design.
Experience using AI-assisted development tools responsibly to improve engineering velocity, code quality, testing, and operational efficiency.
Experience supporting Machine Learning, Generative AI, feature engineering, and AIready data access patterns.
Experience with Docker, Kubernetes, Terraform, or CloudFormation.
Experience with metadata management, data catalogs, lineage, data observability, and data product governance.
Experience in Healthcare, HealthTech, SaaS, or other regulated industries.

Equal Opportunity Employer This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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