Senior Data Engineer
New
K
Karoo HealthHealthcare technology
Pittsburgh preferred, or remote, U.S.-basedFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- Minimum 5 years of dedicated professional experience in a Data Engineering role
- Required Skills
- AWSPythonSQLApache AirflowSnowflakeSparkCI/CDScalaHIPAA
Requirements
- Bring deep, hands-on experience with healthcare data standards and common data models such as TUVA, OMOP, or FHIR.
- Have experience designing core data models and schemas from scratch and translating requirements into scalable data structures.
- Have experience mapping raw healthcare data to standardized models and resolving data quality, normalization, terminology, and structural inconsistencies.
- Have hands-on experience integrating directly with EMR/EHR platforms; eClinicalWorks, AthenaOne, and Epic are examples.
- Have experience with healthcare data regulations such as HIPAA and HITRUST and data formats such as FHIR.
- Hold a Bachelor’s degree in Computer Science, Software Engineering, or a related field, or have equivalent work experience.
- Have at least 5 years of professional Data Engineering experience.
- Demonstrate expert SQL proficiency and proficiency in Python or Scala for data processing.
- Have deep experience with data warehouses such as Snowflake, Google BigQuery, or AWS Redshift, and data lake technologies such as S3 or Delta Lake.
- Have hands-on experience with Apache Spark or Dask.
- Understand cloud platforms and cloud-native development; AWS is preferred, with services such as S3, Lambda, and RDS.
- Have hands-on experience with Apache Airflow or AWS Step Functions for workflow orchestration.
- Bring knowledge of system architecture, scalability, and data-system performance optimization.
- Have experience with test automation, CI/CD, and DevOps practices for data deployments.
- Be able to work independently and make technical decisions.
Responsibilities
- Lead the design, construction, installation, and optimization of reliable, scalable, and secure data architecture.
- Design and evolve foundational healthcare data models and schemas using standards such as TUVA, OMOP, and FHIR.
- Build and maintain production-grade pipelines that ingest, process, enrich, and normalize healthcare data.
- Establish data quality standards, monitoring, and validation processes for analytics data.
- Optimize data processing and retrieval through query tuning, indexing, and partitioning.
- Design and deploy scalable, secure cloud infrastructure using infrastructure-as-code practices.
- Apply healthcare data security practices and ensure compliance with regulations such as HIPAA and HITRUST.
- Develop direct, bi-directional integrations with electronic medical record platforms.
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