Senior Data Engineer - (Remote)

Position Overview

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 & Skills

• 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. Pay is based on several factors, including but not limited to current market conditions, location, education, work experience, certifications, etc. 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).