Swoop
Swoop
Swoop dezvoltă soluții de marketing pentru organizații din domeniul farmaceutic și al științelor vieții, concentrându-se pe interacțiunea directă cu consumatorii și pe implicarea profesioniștilor din domeniul sănătății. Activitatea sa combină inteligența artificială, datele și campaniile omnicanal concepute cu respectarea confidențialității, pentru a contribui la conectarea pacienților, profesioniștilor din domeniul sănătății și brandurilor prin canale precum rețelele sociale și televiziunea. Compania aplică această abordare pentru a îmbunătăți eficiența marketingului și pentru a susține o comunicare din domeniul sănătății mai centrată pe pacient.

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.

Descriere

  • 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

Cerințe

  • 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

Beneficii

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

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