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Data Engineer to build and optimize large-scale data processing systems using Apache Spark and PySpark with client in investment management indsutry

Toronto, ON
  • À discuter
  • Emploi Contrat

  • Publié il y a 11 jour(s)

  • 1 poste à combler dès que possible

Hours: 37.5

Contract: 6 months + possibility of extension

Work Model: 3-4 days onsite a week


Must Haves

  • Strong Python with PySpark for building data solutions
  • Hands-on experience with Apache Spark in cloud-native environments
  • Expertise working with large-scale data systems and modern formats such as Parquet and Iceberg
  • Experience using Databricks for development and optimization

Nice to Have

  • Experience with AWS data services such as Glue or Lake Formation
  • Knowledge of workflow orchestration tools like Airflow
  • Background in distributed data processing architectures
  • Exposure to capital markets or financial data environments

Responsibilities

  • Develop and optimize Spark-based workloads in a cloud setting
  • Work with large-scale datasets using efficient storage and table formats
  • Collaborate with stakeholders to translate data requirements into engineering deliverables
  • Ensure high availability, reliability, and maintainability of data platforms
  • Contribute to production readiness through monitoring, documentation, and deployment
  • Operate independently with minimal supervision to deliver complex data solutions
  • Proactively manage risks and communicate progress to project leads
Disclaimer:
AI may be used in evaluating candidates.
This posting is for an existing vacancy.
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