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Analytics Platform Engineer

Posted 2024-11-14

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💎 Seniority level: Senior, 4+ years

🔍 Industry: Healthcare

🏢 Company: Clover Health

⏳ Experience: 4+ years

Requirements:
  • 4+ years of experience as an Analytics Platform Engineer, Data Platform Engineer, Data Engineer, or similar role.
  • Proficiency in writing Python and SQL transforms (preferably Postgres or BigQuery).
  • Experience developing pipelines for real-time and batch processing using Airflow, event-driven architecture, and Python workflows.
  • Experience with techniques like parallelization, sharding, and windowing to handle larger data sets.
  • Extensive experience with cloud-hosted databases in Google or AWS.
  • Preferred familiarity with healthcare code sets (ICD, SNOMED, RXNORM, LOINC).
  • Knowledge of HIPAA, HITRUST, or SOC2 standards is a plus.
Responsibilities:
  • Develop the underlying and foundational data pipelines to support Analytics and BI engineers.
  • Build transforms in both Python and SQL (BigQuery) to provide users a longitudinal view of patient health.
  • Build scalable pipelines to handle increasing amounts of data and complexity.
  • Support insights into population health, clinician performance, and patient outcomes.
  • Create well-structured database models that are easy to query and understood by team members.
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📍 Hong Kong

🧭 Full-Time

🔍 Healthcare

🏢 Company: Clover Health

  • 4+ years of experience as an active Analytics Platform Engineer, Data Platform Engineer, Data Engineer, or a similar role.
  • Experience writing Python and SQL transforms, preferably in Postgres or BigQuery.
  • Development of pipelines for real-time and batch processing using Airflow DAGs, event-driven architecture, and Python workflows.
  • Experience with parallelization, sharding, windowing, or other strategies for large data sets.
  • Extensive experience with cloud-hosted databases in Google or AWS.
  • Preferred experience with common healthcare code sets like ICD, SNOMED, RXNORM, LOINC.
  • Knowledge of HIPAA, HITRUST, or SOC2 standards is a plus.

  • Develop the underlying and foundational data pipelines to support Analytics and BI engineers.
  • Build transforms in both Python and SQL (BigQuery) to provide users with a longitudinal view of patient health.
  • Build scalable pipelines that can handle increasing amounts of data and complexity.
  • Support insights into population health, clinician performance, and patient outcomes for internal and external consumers.
  • Create well-structured database models that are easy to query and understand by many team members.

AWSPythonSQLKafkaAirflowPostgresCollaboration

Posted 2024-10-17
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