[Hiring] Senior Data Engineer @IKS Health Career

Role Description

IKS Health is seeking a Senior Data Engineer who will contribute to the development and deployment of our AI and machine learning infrastructure. You will be hands-on, working with a team of talented engineers and scientists to build and maintain the cloud-based data infrastructure and platforms that bring our data science models to life. This role requires a strong data engineering background and a passion for the practical application of machine learning in real-world, high-performance applications.

Key Responsibilities

• Data Platform & Pipeline Engineering
  • Design, develop, and maintain robust ELT/ETL pipelines ingesting clinical, claims, and operational data from diverse sources including EHRs, HL7 FHIR APIs, EDI feeds, and third-party SaaS platforms.
  • Build and optimize data models in cloud-based data warehouses (e.g., BigQuery) to support analytics, reporting, and ML workflows.
  • Implement and manage orchestration frameworks to ensure reliable, monitored, and observable data workflows.
  • Develop streaming and real-time data pipelines.
• Cloud Infrastructure & Architecture
  • Architect and provision cloud data infrastructure on GCP using infrastructure-as-code tools.
  • Optimize cloud resource usage for cost efficiency without compromising performance or reliability SLAs.
  • Design and enforce data lake and lakehouse patterns (e.g., Delta Lake, Apache Iceberg) to support structured and semi-structured healthcare data at scale.
• Healthcare Data & Compliance
  • Ensure all data systems comply with HIPAA, HITECH, and applicable state privacy regulations, including implementation of data masking, de-identification, and audit logging.
  • Work with clinical and compliance teams to maintain data governance standards, including data lineage, cataloging and access controls.
  • Apply expertise in healthcare interoperability standards including HL7 v2/v3, FHIR R4, ICD-10, SNOMED CT, and LOINC to integrate and normalize disparate clinical datasets.
• Data Quality & Observability
  • Implement data quality frameworks and validation rules to detect anomalies, schema drift, and completeness issues in healthcare datasets.
  • Build data observability dashboards and alerting to proactively identify and resolve pipeline failures or data degradation before downstream impact.
  • Establish testing standards for data pipelines, including unit tests, integration tests, and data contract validation.
• Collaboration & Technical Leadership
  • Partner with data scientists, analysts, and ML engineers to design datasets and feature stores that support predictive modeling and clinical decision support tools.
  • Mentor junior data engineers through code reviews, architectural guidance, and documentation of best practices.
  • Contribute to and drive adoption of team engineering standards, including CI/CD practices for data pipelines.

Qualifications

• Brings 5+ years of professional data engineering experience, with at least 2 years focused on cloud-native environments.
• Advanced proficiency in Python and SQL for data pipeline development and transformation logic.
• Hands-on experience with a modern data warehouse platform (Snowflake, BigQuery, or Redshift).
• Experience with dbt (data build tool) or equivalent transformation frameworks.
• Demonstrated knowledge of healthcare data standards, including HL7 FHIR, and familiarity with HIPAA compliance requirements.
• Strong experience with workflow orchestration tools such as Apache Airflow, Prefect, or Dagster.
• Proficiency with infrastructure-as-code (Terraform or equivalent) and containerization (Docker, Kubernetes).
• Solid understanding of data modeling principles, including dimensional modeling and data vault techniques.
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.

Preferred Qualifications

• Experience working with Electronic Health Record (EHR) systems such as Epic, Cerner, or Allscripts.
• Familiarity with FHIR-native platforms (e.g., Azure Health Data Services, Google Cloud Healthcare API, or AWS HealthLake).
• Cloud certification in AWS, Azure, or GCP (e.g., AWS Certified Data Analytics, Google Professional Data Engineer).
• Background in real-time/streaming architectures using Apache Kafka, Kinesis, or Pub/Sub.
• Experience with ML feature stores (Feast, Tecton) or MLOps pipelines supporting clinical AI applications.

Compensation and Benefits

• The maximum annual salary range is $135,000-$165,000 a year, determined by years of relevant experience, skills, and the specific geographical location where the work is performed.
• IKS Health offers a competitive benefits package including healthcare, 401(k), and paid time off (all benefits are subject to eligibility requirements for full-time employees).