Swoop
Swoop
Swoop фармацевтикалық және өмір туралы ғылымдар саласындағы ұйымдарға арналған маркетингтік шешімдер әзірлейді және тұтынушылармен тікелей әрі медицина қызметкерлерімен өзара байланысқа назар аударады. Компанияның жұмысы әлеуметтік желілер мен теледидар сияқты арналар арқылы пациенттерді, медицина қызметкерлерін және брендтерді байланыстыруға көмектесу үшін жасанды интеллектіні, деректерді және құпиялылықты ескеретін омниканалды науқандарды біріктіреді. Компания бұл тәсілді маркетинг тиімділігін арттыру және пациентке бағдарланған денсаулық сақтау коммуникациясын қолдау үшін қолданады.

Senior Data Engineer at Swoop — Toronto Hybrid

Lead NimbleRx’s compliant healthcare data platform, developing scalable pipelines, warehouse models, and AI tools that support pharmacy and patient-engagement operations.

Сипаттама

  • Own the full data platform lifecycle, from ingestion and transformation through storage, querying, and access
  • Shape the data platform roadmap as the company’s data requirements expand
  • Build and improve batch and streaming pipelines with PySpark/EMR, Kinesis, Lambda, and Step Functions
  • Bring data from Postgres, Salesforce, external vendors, and product event streams into an Iceberg-based lake
  • Define SCD tables, event tables, and data standards for engineering and analytics teams
  • Work with product, engineering, analytics, and operations partners to turn data needs into dependable pipelines
  • Create documentation and tools that enable other teams to work independently with data
  • Manage security and compliance capabilities, including audit logs, access controls, and temporary-access processes
  • Improve backend query performance in Java/Spring services through replica routing, indexing, caching, and I/O instrumentation
  • Investigate and resolve IOPS spikes, pipeline failures, schema drift, and delayed data
  • Apply AI to pipeline scaffolding, schema development, and ad hoc investigations
  • Deliver internal AI tools for use by other teams
  • Coach engineers and analysts on effective use of the data platform

Талаптар

  • At least five years of experience building production data pipelines and data platforms
  • Advanced Python, PySpark, and SQL skills, including tuning Spark workloads at scale
  • Ability and willingness to contribute to Java and Spring Boot services surrounding the data layer
  • Practical experience with distributed computing such as Spark/EMR, streaming through Kinesis, and object storage on S3
  • Strong Postgres knowledge, including query tuning, indexing, replication, replica routing, and diagnosing database bottlenecks
  • Experience with Iceberg and Trino, or comparable technologies
  • Familiarity with CI/CD and Terraform
  • Experience building with AI, frontier models, or agentic coding tools
  • Demonstrated ability to collaborate across product, operations, and other teams
  • Current authorization to work in Canada is strongly preferred
  • Willingness to treat security and PII/PHI handling as core engineering responsibilities

Артықшылықтар

  • Opportunities for professional development
  • Hybrid working arrangement
  • Visa sponsorship may be considered exceptionally for highly qualified candidates with specialized skills

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