Data Engineer, Sr.

Experity is a mission-driven organization dedicated to transforming on-demand healthcare across the United States. The company empowers urgent care clinics with industry-leading software solutions designed to make healthcare delivery faster, easier, and more patient-centric. By providing innovative technology platforms, Experity aims to streamline operations, enhance patient experiences, and support healthcare providers in delivering high-quality care. Joining Experity offers an opportunity to be part of a forward-thinking team committed to making a meaningful impact on healthcare delivery, impacting millions of lives through improved access and operational excellence. The company's culture emphasizes collaboration, innovation, and continuous learning, fostering an environment where employees can grow professionally while contributing to a vital industry.

About the role

We are seeking a highly skilled Senior Data Engineer to join our dynamic team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and platforms that power Experity’s analytics, AI/ML initiatives, and healthcare products. This position requires a hands-on approach with a strong foundation in data engineering, cloud technologies, distributed data processing, and software engineering principles. As a senior member of the team, you will collaborate closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform diverse data sources into high-quality, trusted, and reusable data assets. Your leadership will be instrumental in guiding architecture decisions, mentoring junior engineers, and continuously enhancing the scalability, reliability, and efficiency of our data ecosystem. The role offers an exciting opportunity to work with cutting-edge technologies and contribute to innovative healthcare solutions that impact millions of lives.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
• Minimum of 5+ years of experience building production-grade data pipelines, data platforms, and large-scale data processing solutions.
• Proficiency in Python and SQL with strong software engineering fundamentals.
• Hands-on experience with Snowflake and cloud-based data platforms.
• Experience with distributed and streaming technologies such as Kafka, Flink, or similar.
• Strong knowledge of AWS services including S3, Lambda, Glue, Kinesis, or equivalent cloud technologies.
• Expertise in designing and optimizing ETL/ELT pipelines, data models, and high-volume data workflows.
• Experience with orchestration tools like Airflow or similar platforms.
• Familiarity with CI/CD pipelines, Git, automated testing, and Infrastructure as Code.
• Understanding of data quality, governance, security, observability, and production support.
• Excellent problem-solving, communication, and cross-functional collaboration skills.
• A “full-stack mindset” with the ability to solve problems end-to-end.
• Preferred experience with dbt or dbt cloud, AI-native engineering environments, and supporting ML workloads.
• Experience with Docker, Kubernetes, Terraform, or CloudFormation is a plus.
• Knowledge of data cataloging, lineage, metadata management, and data observability platforms.
• Experience working in Healthcare, HealthTech, SaaS, or other regulated industries is advantageous.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for both batch and near-real-time data processing.
• Integrate data from various sources including databases, APIs, applications, event streams, and external data providers into Experity’s enterprise data platform.
• Create reusable, high-quality data models and curated data products to support analytics, reporting, AI/ML models, and operational needs.
• Develop complex data transformations and processing workflows utilizing Python, SQL, Snowflake, and distributed data technologies.
• Architect data solutions focusing on scalability, availability, resiliency, performance, and cost efficiency.
• Implement DataOps best practices by developing reusable frameworks, libraries, and engineering patterns to improve developer productivity and pipeline consistency.
• Establish monitoring, alerting, data observability, and automated remediation systems to ensure pipeline reliability and data integrity.
• Troubleshoot and resolve complex production issues, conducting root cause analysis and implementing long-term improvements.
• Continuously optimize data pipelines, queries, storage, and compute resources for performance and cost management.
• Ensure data quality, validation, lineage, and reconciliation controls are in place across critical pipelines.
• Partner with Data Architecture, Governance, and Security teams to ensure compliance with enterprise standards and healthcare data security regulations.
• Provide technical leadership through solution design, architecture discussions, code reviews, and best practices sharing.
• Mentor junior Data Engineers, fostering technical growth and engineering excellence within the team.
• Collaborate with Data Scientists, Machine Learning Engineers, Product, and Business stakeholders to translate requirements into scalable data solutions.
• Document technical processes, data pipelines, architecture, and operational procedures clearly and comprehensively.

Benefits

• Day-One comprehensive health, dental/orthodontia, and vision coverage.
• Ownership and impact through a synthetic ownership program after one year.
• Access to Employee Assistance Program for mental wellness, financial coaching, pet care, vacation planning, and more.
• Generous paid time off, team events, family picnics, and holiday celebrations.
• Development programs designed to support career growth and skill enhancement.
• Competitive compensation package, including quarterly bonuses and 401(k) matching.
• Opportunities for professional growth and leadership development within a global organization.
• Participation in a dynamic, inclusive, and innovative company culture that values diverse perspectives.