Data Engineer

The Data Engineer is central to building our future-state architecture by modernizing how public health data moves, transforms, and informs decision-making at scale. You will lead the design and implementation of next-generation pipelines, ensure data reliability and compliance, and guide integration teams through migration from legacy systems. 

As part of a collaborative, agile team, you’ll work closely with data architects, integration engineers, data scientists, and product stakeholders to deliver solutions that directly impact public health outcomes. The ideal candidate thrives in complex data environments, is motivated by meaningful mission-driven work, and brings both technical depth and mentorship skills to elevate our interoperability platform. 

• Play a key role in shaping the future of our data interoperability platform. 
• Design and operatesecure, high-performance data pipelines for real-time and batch public health data flows. 
• Architect and implement scalable solutions that move sensitive health data reliably and meet strict security and compliance standards. 
• Build and optimizeETL/ELT pipelines using NiFi, Kafka, Python, and SQL. 
• Collaborate with interoperability, product, and data science teams to migrate legacy pipelines to modern architectures. 
• Fine-tunedata lakes and ensure smooth data exchange across systems. 
• Define monitoring and alerting strategies and create runbooks to support operational teams. 
• Troubleshoot production issues to maintainstable and performant pipelines. 
• Drive continuous improvement across the data ecosystem through collaboration, innovation, and strong execution. 
• Contribute directly to building and delivering high-quality, scalable integrations that drive rapid product progress. 
• Collaborate closely with teammates to share knowledge and ensure smooth, efficient development workflows. 

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field  
• A minimum of 3 years of experience implementing enterprise-grade data pipelines OR 7 years of equivalent professional experience implementing enterprise-grade data pipelines 
• Someone who thrives at the intersection of technical complexity and mission-driven impact. 
• Proven ability to build robust, production-grade pipelines from the ground up and work confidently with distributed data systems. 
• A curious, proactive problem solver who excels in fast-paced, agile environments. 
• Hands-on expertise with NiFi, Kafka, Python, and SQL, including designing, operating, and optimizingETL/ELT pipelines in the cloud. 
• Experience using or integrating with OpenSearch/Elasticsearch. 
• Familiarity with CI/CD and DevOps practices; able to partner with DevOps/SRE to integrate pipelines into existing tooling (not responsible for platform design). 
• Practical experience using relational databases and existing schemas (implementing against established data models; extending under guidance). 
• Strong understanding of data security and compliance requirements for sensitive data. 
• Excellent cross-functional collaborator with clear communication and strong technical documentation skills. 
• A growth mindset with a passion for solving complex interoperability challenges elegantly and efficiently. 
• Strong communication skills to translate complex engineering concepts into clear strategies for cross-functional partners.

• Deep technical expertise paired with a strong understanding of public health data environments. 
• Experience with healthcare data standards such as HL7 v2.x, FHIR, and terminologies like LOINC, CVX, SNOMED, and ICD-10. 
• Proven success building event-driven architectures with Kafka or implementing data de-identification strategies. 
• Hands-on experience with integration engines (e.g., Rhapsody, Mirth) and containerized deployments (e.g., Docker, Kubernetes). 
• Demonstrated ability to scale data platforms in production environments. 
• Familiarity with Master Patient Index (MPI) solutions or data deduplication frameworks. 
• Bring a proactive mindset—anticipating challenges, designing with scalability and security in mind, and delivering solutions that accelerate time to product. 

Benefits and Perks:  InductiveHealth offers competitive benefits and perks including:

·       Virtual first, remote organization and culture

·       Flexible Paid Time Off (PTO)

·       401(k) retirement plan with corporate matching

·       Medical, prescription, vision, and dental coverage (multiple plans based on your needs)

·       Short Term and Long Term Disability (for employee) 

·       Life Insurance (for employee)

·       New Team Member support for home office setup

Target Salary Bands: Each team member’s compensation decisions are based on several inputs, and we expect many of the candidates who are offered positions to fall within the advertised salary band. We recognize that the team member hired may be less (or more) experienced than the posted job description therefore impacting compensation decisions.

About InductiveHealth: InductiveHealth (www.inductivehealth.com) was co-founded by Matthew Dollacker and Stephen Macauley in 2013.  Today, InductiveHealth is headquartered in Atlanta, Georgia and has over 80 team members across the United States supporting state, tribal, local, and territorial (STLT) public health agencies in addition to Federal agencies such as the Centers for Disease Control and Prevention (CDC).  In early 2021, InductiveHealth became the exclusive commercial partner of Johns Hopkins University Applied Physics Laboratory (JHU/APL) for the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) syndromic surveillance solution.  To accelerate growth in the wake of the COVID-19 pandemic, InductiveHealth become a portfolio company of Diversis Capital (https://www.diversis.com/) in early 2022.

All responses to applications will come from [email protected] or from the domain @inductivehealth.com. 

InductiveHealth is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to their race, color, religion, sex, sexual orientation, gender identity or expression, age, national origin, or disability.