Data Engineer to build and optimize large-scale data processing systems using Apache Spark and PySpark with client in investment management indsutry
S.i. Systems
Toronto, ON- Salary To be discussed
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Contract job
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Published since 11 day(s)
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1 position to fill as soon as possible
Description
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
AI may be used in evaluating candidates.
This posting is for an existing vacancy.
Requirements
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