Cloud and Systems Integration Developer
MaxonBuild Azure infrastructure and enterprise integrations supporting Maxon’s creative software operations. Automate deployments, identity workflows, and system connections across the organization.
Open
TD is a major North American bank serving individuals, businesses, and institutional clients through personal and business banking, insurance, wealth management, and securities services. Its broad operating model supports career opportunities across banking and finance, with roles spanning different regions and areas of expertise. TD also emphasizes sustainability, diversity, equity, inclusion, and community impact, shaping a workplace culture centered on care, respect, and employee growth.
Senior Data Engineer (Scala, Spark, Python) – TD, Toronto Hybrid
Join TD Securities as a Senior Data Engineer supporting capital markets risk platforms. Build and maintain scalable real-time data systems and analytics infrastructure with Scala, Python, and Spark.
Description
- Design distributed data processing systems with Scala, Python, and Apache Spark
- Develop and optimize large-scale batch and streaming Spark pipelines
- Translate data needs from scientists, analysts, and stakeholders into effective solutions
- Maintain real-time processing systems using Scala, Spark, PySpark, and Akka/Pekko
- Create and support ETL workflows that transform and integrate data from multiple sources
- Support data platforms for Credit Risk, Counterparty Credit Risk, XVA, and Regulatory Reporting
- Apply Databricks Unity Catalog, lineage, classification, and access governance practices
- Use FpML, financial product modeling, and capital markets reference data standards
- Protect data quality, reliability, and integrity through automated testing and monitoring
- Partner with DevOps teams to deploy and operate CI/CD and cloud-based data pipelines
- Improve Spark performance and scalability through job optimization and tuning
- Contribute to code reviews and strengthen engineering practices
- Keep current with evolving data engineering tools and methods
- Communicate effectively with technical and non-technical colleagues
- Develop strong partnerships across business and technology teams to improve productivity and operational effectiveness
Requirements
- Bachelor’s or master’s degree in computer science, engineering, or a related discipline
- At least five years of data engineering experience, particularly with Python, Scala, and Spark
- Solid knowledge of data warehousing, data modeling, and ETL practices
- Practical experience with Azure ADLS, Azure Databricks, and Dremio
- Practical experience with Hadoop, Kafka, Hive, and HBase
- Practical experience using Akka/Pekko to build distributed systems
- Understanding of REST and gRPC communication protocols
- Strong SQL skills and experience with relational and NoSQL databases
- Experience with GCP or Azure and Docker or Kubernetes is an advantage
- Experience with Apache Kafka or Confluent is an advantage
- Proficiency in C# for Excel add-in development
- Experience building CI/CD pipelines and using infrastructure as code
- Knowledge of data governance and security practices
- Familiarity with machine learning and data science workflows
- Experience with real-time analytics and event-driven architectures
- Strong problem-solving ability with the capacity to work independently and collaboratively
- Clear communication skills and experience working across functions
- Demonstrated ability to collaborate effectively with global teams
- Experience succeeding in fast-paced environments while adapting to business priorities
- Knowledge of derivatives pricing and capital markets is an advantage
Benefits
- Discretionary variable compensation tied to business and individual performance
- Health and wellness benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development opportunities
- Reward and recognition programs
- Ongoing development discussions, training, and access to an online learning platform
- Mentoring programs
- Training and onboarding sessions
- Workplace accommodations such as accessible meeting rooms and captioning for virtual interviews
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