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InductiveHealth

Public health data infrastructure and surveillance

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • At least 3 years of experience implementing enterprise-grade data pipelines, or 7 years of related professional experience in software, data, or integration engineering that includes building and operating production data pipelines.
  • Hands-on expertise with NiFi, Kafka, Python, and SQL, including designing, operating, and optimizing cloud ETL/ELT pipelines.
  • Ability to build robust, production-grade pipelines from the ground up and work with distributed data systems.
  • Hands-on experience deploying and operating data pipelines in Azure or AWS, including secure handling of sensitive data through IAM/RBAC, encryption, and secrets management.
  • Experience implementing CI/CD best practices for data pipelines with GitHub and GitHub Actions, including NiFi flow versioning and promotion with NiFi Registry, automated testing, and peer-reviewed releases.
  • Ability to partner with DevOps/SRE to integrate pipelines into existing tooling; overall platform design is outside this role's responsibility.
  • Experience using or integrating with OpenSearch or Elasticsearch.
  • Practical experience using relational databases and existing schemas, implementing against established data models and extending them under guidance.
  • Strong understanding of data security and compliance requirements for sensitive data.
  • Clear communication and technical documentation skills, including translating complex engineering concepts into strategies for cross-functional partners.

Responsibilities

  • Shape the future of the data interoperability platform.
  • Design and operate secure, 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 optimize ETL/ELT pipelines using NiFi, Kafka, Python, and SQL.
  • Build and maintain CI/CD pipelines for NiFi flows, Python, and SQL using GitHub and GitHub Actions, including flow versioning through NiFi Registry and automated promotion across development, test, and production.
  • Deploy and operate data pipelines on Azure and AWS, partnering with DevOps/SRE to integrate them into existing cloud infrastructure and tooling.
  • Apply CI/CD practices including pull request reviews, branch protection, automated testing and validation, parameterized environment configuration, and versioned releases with rollback.
  • Collaborate with interoperability, product, and data science teams to migrate legacy pipelines to modern architectures.
  • Fine-tune data lakes and ensure smooth data exchange across systems.
  • Define monitoring and alerting strategies, such as Grafana dashboards and alerts, and create runbooks to support operational teams.
  • Troubleshoot production issues to maintain stable and performant pipelines.
  • Improve the data ecosystem through collaboration, innovation, and execution.
  • Build and deliver scalable integrations that drive product progress.
  • Share knowledge with teammates and support efficient development workflows.

Desired Qualifications

  • Deep technical expertise paired with an understanding of public health data environments.
  • Experience with healthcare data standards such as HL7 v2.x and FHIR, and terminologies such as LOINC, CVX, SNOMED, and ICD-10.
  • Success building event-driven architectures with Kafka or implementing data de-identification strategies.
  • Hands-on experience with integration engines such as Rhapsody or Mirth and containerized deployments such as Docker or Kubernetes.
  • Experience with infrastructure as code, including Terraform, Bicep, or CloudFormation, and automated deployment of NiFi or Kafka environments.
  • Experience with monitoring and observability for data pipelines using Grafana and cloud-native tools such as Azure Monitor or CloudWatch.
  • Demonstrated ability to scale data platforms in production environments.
  • Familiarity with Master Patient Index (MPI) solutions or data deduplication frameworks.

About the Company

InductiveHealth

Public health data infrastructure and surveillance

InductiveHealth Informatics provides data infrastructure, surveillance, and intervention services for public health agencies, focusing on disease and syndromic surveillance and managing many jurisdictional systems on platforms like the NEDSS Base System and ESSENCE. Its offerings help public health teams collect, process, and analyze health data to detect outbreaks and trends, including tools like the COVID-19 Data Tracker that aggregates multiple sources for up-to-date epidemiology. The company differentiates itself by handling more jurisdictional surveillance systems than any competitor and by delivering end-to-end technology and services that integrate with established surveillance platforms for federal, state, tribal, local, and territorial health entities. Its goal is to enable government health agencies to monitor and respond to public health threats with accurate, timely, and actionable disease data through scalable surveillance solutions.

Company size
51-200
Company stage
Acquired
Total funding
Not listed
Headquarters
Atlanta, GA
Founded
2013

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