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Senior Research Data Engineer (Canada)

1 month, 2 weeks ago
Canada
Full-time
Senior
Data Engineer
Data Science and Analytics
Apache Airflow Apache Spark AWS Azure CI/CD Dagster Databricks dbt Git HIPAA MLflow Prefect Python PyTorch SQL
Apply Now
PointClickCare

PointClickCare

PointClickCare provides a leading cloud-based healthcare software platform that enables long-term and post-acute care providers to effectively manage the complete lifecycle of resident care while enhancing operational efficiency and improving resident ...

Health Care Providers & Services
1K-5K
Founded 2000
$232M raised
View All Jobs 68

Description

  • Own the gold data layer that transforms silver tables into curated, semantically rich, documented datasets for AI model development.
  • Reverse-engineer data semantics by working with product engineers, clinical experts, and workflow experts to understand source systems and data behavior.
  • Bridge researcher needs with data design by translating AI applied research requirements into reusable gold data products.
  • Curate datasets across modalities, including structured tables and unstructured content for generative AI, RAG, predictive modeling, and classical ML use cases.
  • Build reusable transformation pipelines from silver to gold in Databricks/Spark as scheduled and observable workloads.
  • Automate data quality, filtering, labeling, synthesis, and weak supervision workflows for AI research data preparation.
  • Maintain reproducible dataset snapshots, lineage, and semantic definitions for downstream AI R&D teams.
  • Document datasets, transformations, provenance, and quirks so others can reliably reuse the data assets.
  • Collaborate with AI researchers, data platform teams, product teams, and clinical/workflow experts across the R&D lifecycle.
  • Support model development, experimentation, evaluation, and operational sustaining by delivering AI-ready data assets.

Requirements

  • 5+ years building production data systems, including at least 2 years supporting ML or AI workloads.
  • Advanced Python, SQL, and PySpark/Databricks experience for large, messy data.
  • Expert-level SQL ability, including reading complex stored procedures and reverse-engineering business logic from queries.
  • Strong Databricks ecosystem experience, including Delta Lake, Unity Catalog, Spark/PySpark tuning, and MLflow.
  • Working knowledge of AI concepts such as embeddings, tokenization, feature engineering, point-in-time correctness, data drift, and train/validation/test splits.
  • Experience transforming unstructured content such as text, PDFs, transcripts, and logs into model-ready data.
  • Experience with AI-friendly formats and storage layouts such as Parquet and Hugging Face datasets, including partitioning, sharding, and caching.
  • Experience with pipeline orchestration and dataset versioning tools such as Airflow, Databricks Workflows, Dagster, or Prefect.
  • Experience handling regulated or sensitive data under controlled access, such as HIPAA or equivalent, with familiarity in de-identification concepts.
  • Git-based version control and CI/CD experience for data and code.
  • Strong written documentation skills and ability to elicit requirements from technical and non-technical experts.
  • Bachelor’s degree in computer science, data science, engineering, statistics, or a related field, or equivalent practical experience.
  • Preferred: hands-on EHR data experience in skilled nursing, long-term care, post-acute care, or senior living.
  • Preferred: working knowledge of clinical terminologies and standards such as ICD-10, SNOMED CT, LOINC, HL7v2, FHIR, and CCDA.
  • Preferred: dbt experience for transformation and testing.
  • Preferred: familiarity with training-side ML frameworks such as PyTorch and experience supporting LLM or foundation-model training/fine-tuning pipelines.
  • Preferred: experience with clinical NLP, OCR, document parsing, or ASR/transcript pipelines.
  • Preferred: experience with data lineage and catalog tools.
  • Preferred: prior experience embedded within an AI or ML research team.
  • Preferred: master’s degree in a relevant quantitative or computer science field.

Benefits

  • Benefits starting from Day 1.
  • Retirement plan matching.
  • Flexible paid time off.
  • Wellness support programs and resources.
  • Parental and caregiver leave.
  • Fertility and adoption support.
  • Continuous development support program.
  • Employee assistance program.

Interested in this position?

Apply directly on the company website

Apply Now

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