Senior Data Engineer - Remote

Job Description

Senior Data Engineer - Remote - Experity | Built In Companies Jobs Articles Can't find your company? Create a company profile. View All Jobs Join Log In For Employers Experity Jobs Senior Data Engineer - Remote Experity Senior Data Engineer - Remote Posted 2 Days Ago Hiring Remotely in Machesney Park, IL, USA In-Office or Remote 110K-150K Annually Senior level Healthtech • Software The Role Design, build, and operate scalable ETL/ELT pipelines and data platform capabilities to support analytics, AI/ML, and product needs. Lead technical designs, mentor engineers, implement DataOps/CI/CD and observability, ensure data quality/governance/security, and optimize performance and cost across cloud-based data systems. Summary Generated by Built In 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. Why You’ll Love Working Here At Experity, great work starts with great people—and we go the extra mile to support our team with a culture of care, growth, and celebration: Day-One Benefits: Health, dental/orthodontia, and vision coverage the moment you start. Ownership & Impact: Be part of our success with a synthetic ownership program after one year. Robust Support: Access our Employee Assistance Program for everything from mental wellness to financial coaching. Pets, planning a vacation, and more . Recharge & Reconnect: Generous PTO, team events, family picnics, and holiday parties. Career Growth: Development programs designed to help you thrive and grow. Competitive Compensation: Including quarterly bonuses and 401(k) matching to invest in your future. Position Type : Full-time Compensation : $110,000-$150,000, based on experience Location : Remote: Team members who live within the U.S. but are not local within a commutable distance from one of our offices may work remotely, with occasional travel to an Experity office for meetings, team collaboration or as needed. Position Overview We are seeking a Senior Data Engineer to design, build, and operate scalable data pipelines and data platform capabilities that power Experity's analytics, AI/ML, and healthcare products. This is a hands-on engineering role requiring strong expertise in data engineering, cloud technologies, distributed data processing, and software engineering. You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform data from diverse sources into trusted, high-quality, and reusable data products. As a senior member of the team, you will also provide technical leadership, mentor engineers, contribute to architecture and design decisions, and continuously improve the scalability, reliability, and efficiency of Experity's data ecosystem. What You'll Do Data Engineering & Platform Design, build, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing. Integrate data from databases, APIs, applications, event streams, and external sources into Experity's enterprise data platform. Build reusable, high-quality data models and curated data products for analytics, reporting, AI/ML, and operational applications. Develop complex data transformations and processing workflows using Python, SQL, Snowflake, and distributed data technologies. Design data solutions for scalability, availability, resiliency, performance, and cost efficiency. Engineering Excellence & DataOps Develop reusable frameworks, libraries, and engineering patterns that improve developer productivity and data pipeline consistency. Implement automated testing, CI/CD, Infrastructure as Code, and DataOps practices across data engineering workflows. Build monitoring, alerting, data observability, and automated remediation capabilities to ensure pipeline reliability and data integrity. Troubleshoot complex production issues and drive root-cause analysis and long-term improvements. Continuously optimize data pipelines, queries, storage, and compute for performance and cost. Data Quality, Governance & Security Implement data quality, validation, lineage, and reconciliation controls across critical data pipelines. Partner with Data Architecture, Governance, and Security teams to ensure data solutions follow enterpri