Note: The job is a remote job and is open to candidates in USA. Experity is a mission-driven healthcare technology company transforming on-demand care across the United States through software for urgent care clinics. The Senior Data Engineer will design, build, and operate scalable data pipelines and platform capabilities supporting analytics, AI/ML, and healthcare products while providing technical leadership and mentoring. The role also focuses on data quality, governance, security, reliability, and collaboration across engineering, data science, product, and business teams.
Responsibilities
- 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
- 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
- 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 enterprise standards
- Ensure healthcare data is handled securely and in accordance with applicable privacy, security, and compliance requirements
- Provide technical leadership through solution design, architecture discussions, code reviews, and engineering best practices
- Mentor Data Engineers and help improve engineering quality and technical capabilities across the team
- Partner with Data Scientists and Machine Learning Engineers to build reliable datasets, feature pipelines, and data infrastructure for AI/ML applications
- Collaborate with Product, Engineering, Analytics, and business stakeholders to translate requirements into scalable data solutions
- Maintain clear technical documentation for data pipelines, models, architecture, and operational processes
Skills
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field
- 5+ years of experience building production-grade data pipelines, data platforms, and large-scale data processing solutions
- Advanced proficiency in Python and SQL with strong software engineering fundamentals
- Hands-on experience with Snowflake and cloud-based data platforms
- Experience with Kafka, Flink, or other distributed and streaming technologies
- Strong experience with AWS, including services such as S3, Lambda, Glue, Kinesis, or equivalent cloud technologies
- Experience designing and optimizing ETL/ELT pipelines, data models, and high-volume data processing workflows
- Experience with orchestration technologies such as Airflow or equivalent platforms
- Experience with CI/CD, Git, automated testing, and Infrastructure as Code
- Strong understanding of data quality, governance, security, observability, and production support
- Strong problem-solving, communication, and cross-functional collaboration skills
- A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end
- Experience transforming data leveraging dbt, preferably dbt cloud
- Experience working in AI-native engineering environments and effectively leveraging AI-assisted development tools to improve engineering velocity, code quality, and operational efficiency
- Experience supporting Machine Learning and Generative AI workloads, including feature engineering and ML data pipelines
- Experience with Docker, Kubernetes, Terraform, or CloudFormation
- Experience with data cataloging, lineage, metadata management, and data observability platforms
- Experience in Healthcare, HealthTech, SaaS, or other regulated industries
Benefits
- Health, dental/orthodontia, and vision coverage the moment you start.
- A synthetic ownership program after one year.
- Employee Assistance Program support, including mental wellness and financial coaching.
- Generous PTO.
- Team events, family picnics, and holiday parties.
- Development programs designed to help you thrive and grow.
- Quarterly bonuses.
- 401(k) matching.
- Remote work for team members who live within the U.S. but are not local within a commutable distance from one of the offices, with occasional travel to an Experity office for meetings, team collaboration or as needed.
Company Overview
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