Senior Data Engineer :Scala, Spark, Python, Hadoop, Databricks
Role Overview
The Counterparty Credit Risk group is building risk computation platforms to quantify, understand, and reduce external exposure under adverse market conditions.
The XVA and CCR data development team builds and maintains scalable data pipelines for analytics and data-driven applications.
The role supports high-volume computation, Big Data storage, analytics, and data distribution.
Key Skills for This Role
Full Job Posting
Team and role
The Counterparty Credit Risk group is building risk computation platforms to quantify, understand, and reduce external exposure under adverse market conditions.
The XVA and CCR data development team builds and maintains scalable data pipelines for analytics and data-driven applications.
The role supports high-volume computation, Big Data storage, analytics, and data distribution.
Key responsibilities
- Design distributed data processing systems using Scala, Python, and Apache Spark.
- Build and optimize large-scale batch and streaming pipelines.
- Collaborate with data scientists, analysts, and stakeholders to deliver data solutions.
- Maintain real-time processing using Scala, Spark, PySpark, and Akka/Pekko.
- Develop and maintain ETL processes to transform and integrate source data.
- Ensure data quality, reliability, and integrity with automated testing and monitoring.
- Work with DevOps teams to deploy and manage CI/CD and data pipelines in a cloud environment.
- Optimize Spark jobs for performance and scalability.
- Participate in code reviews and improve engineering practices.
- Keep current with data engineering technologies and best practices.
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- At least 5 years of data engineering experience, with a strong focus on Python, Scala, and Spark.
- Strong understanding of data warehousing, data modeling, and ETL processes.
- Hands-on experience with cloud platforms such as Azure ADLS, Azure Databricks, and Dremio.
- Hands-on experience with big data technologies such as Hadoop, Kafka, Hive, and HBase.
- Hands-on experience with Akka/Pekko for distributed systems.
- Experience supporting Credit Risk, Counterparty Credit Risk, XVA, or Regulatory Reporting data platforms.
- Hands-on experience with Databricks Unity Catalog, data lineage, data classification, and access governance frameworks.
- Understanding of FpML, financial product modeling, and Capital Markets reference data standards.
Pay
- Base pay range is CAD $126,800 to $164,100; the role may also be eligible for a discretionary variable compensation award.
Hours
- Scheduled hours are 37.5.
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