We’re hiring a Senior Data Engineer to help build and scale the data foundation of a healthcare technology platform. This role is ideal for someone who combines strong data engineering fundamentals with real healthcare domain experience and understands the regulatory responsibilities that come with healthcare data.
You’ll have meaningful ownership, influence platform design, and help define how healthcare data is ingested, transformed, and delivered.
What You’ll Do
· Design and Architect Data Systems — Lead the design, construction, installation, and optimization of highly reliable, scalable, and secure data architecture.
· Develop Data Pipelines — Build and maintain complex, production-grade pipelines to ingest, process, and enrich large volumes of healthcare data.
· Data Quality and Governance — Establish and enforce data quality standards, monitoring, and validation processes to ensure accuracy, completeness, and consistency of analytics data.
· Performance Optimization — Implement query tuning, indexing, and partitioning strategies to maximize performance and efficiency of data processing and retrieval.
· Cloud Infrastructure — Design and deploy scalable, secure cloud infrastructure using infrastructure-as-code best practices.
· Safeguard Data — Ensure strict compliance with healthcare data regulations (HIPAA, HITRUST) and implement data security best practices.
What We’re Looking For
· Experience with healthcare data regulations (HIPAA, HITRUST) and healthcare data formats (FHIR).
· Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent work experience.
· Minimum 5 years of professional Data Engineering experience, ideally in a startup or fast-paced healthcare technology environment.
· Expert proficiency in SQL and at least one data-processing language (Python or Scala).
· Deep experience designing and managing Data Warehouses (Snowflake, BigQuery, Redshift) and working with Data Lake technologies (S3, Delta Lake).
· Hands-on experience with Big Data processing frameworks such as Apache Spark or Dask.
· Strong understanding of cloud platforms (AWS preferred) and cloud-native development, including services like S3, Lambda, and RDS.
· Experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions.
· Expert knowledge of system architecture, scalability, and performance optimization for data systems.
· Experience with test automation, CI/CD, and DevOps best practices for data deployments.
· Ability to work independently and make high-impact technical decisions.
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