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Tier-1 brand, mid-level generalist title, metro location and attractive skillset drive high competition.
Requires healthcare EHR/claims/lab expertise and domain-specific data models, reducing cross-industry transferability.
Explicit 4+ years plus mandatory healthcare data, Snowflake, Airflow and ETL/ML skills make filters strict.
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Design, build, and maintain ETL/ELT pipelines utilizing Snowflake, Redshift, S3, AWS services, and workflow orchestration tools like Apache Airflow.
Integrate and manage healthcare datasets (EHR, claims, laboratory data) ensuring data quality, lineage, and governance for analytics and AI model operations.
Provide operational support for data solutions, including incident response, performance optimization, and contributing to cloud architecture and data security in healthcare/biopharma context.
Bachelor's or Master's degree in quantitative field (e.g., Computer Science, Data Science, Engineering, Information Systems, Economics).
Minimum 4+ years of relevant experience in data engineering or analytics engineering.
Proficiency in Python, SQL, Snowflake, AWS (S3, Lambda), Amazon Redshift, Apache Spark, Apache Airflow.
Experience with healthcare data types (EMR/EHR, claims, laboratory) and understanding of healthcare data models and compliance is mandatory.
Experienced individual contributor with deep technical expertise in data engineering and AI-first data science problem solving.
Strong familiarity with operationalizing machine learning pipelines and building scalable data services in cloud environments.
Background in healthcare or biopharma data analytics, capable of translating complex domain and business requirements into data-driven solutions.