Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
As a Software Engineer (ETL Development focus) within Client Systems, Canadian Banking Engineering team, you will play a key role in designing, developing, and modernizing enterprise-grade data integration platforms. This includes building scalable batch and distributed data pipelines, enabling high-performance data processing using Spark, and supporting the transformation of legacy ETL workloads into modern, cloud-ready architectures.
This role is ideal for someone who thrives in large-scale data transformation programs, enjoys working on high-volume data pipelines, and is motivated to deliver reliable, performant, and future-ready data integration solutions.
Responsibilities
- Design, develop, and support scalable ETL/data pipelines using tools such as Talend and Apache Spark framework
- Lead and contribute to the migration of legacy ETL workloads to modern frameworks (e.g. Spark )
- Build and optimize large-scale batch and distributed data processing pipelines
- Analyze ETL performance (CPU, memory, I/O, runtime bottlenecks) and implement tuning strategies
- Develop reusable ETL frameworks, components, and orchestration patterns for enterprise use
- Implement data ingestion, transformation, and data quality checks across structured and semi-structured data sources
- Develop and maintain complex SQL transformations, stored procedures, and data models
- Integrate ETL pipelines with enterprise systems using messaging (Kafka/MQ), APIs, and batch orchestration frameworks
- Ensure data integrity, lineage, reconciliation, and auditability across pipelines
- Collaborate with architecture and engineering teams to design target-state data platforms and migration approaches
- Participate in end-to-end system integration and migration testing across distributed platforms
- Contribute to technical design discussions and provide input to stakeholders
- Collaborate with cross-functional teams including data engineering, application support, database, and infrastructure teams
- Mentor junior developers and promote best practices in ETL design, performance tuning, and data engineering
- Ensure adherence to coding standards, version control, and CI/CD practices (Git-based repositories)
Core Technical Skills
- Strong hands-on experience with Talend ETL development
- Strong experience with Apache Spark (PySpark or Scala) for large-scale data processing
- Experience working with distributed data processing and big data frameworks
- Strong Unix/Linux scripting experience for ETL orchestration and automation
Data & Database Skills
- Strong experience with relational databases (DB2, Oracle, or similar)
- Advanced SQL proficiency:
- Complex transformations
- Performance tuning
- Stored procedures
- Experience working with large datasets and data warehousing concepts
ETL & Integration Skills
- Experience with data migration and modernization initiatives (legacy → distributed platforms)
- Experience with:
- Batch processing frameworks
- Data ingestion and transformation pipelines
- API-based integrations
Experience with source control systems (Git, Bitbucket, GitHub)
Migration & Modernization
- Hands-on experience supporting ETL modernization or platform migration programs
- Experience migrating from traditional ETL tools (e.g. Talend, Informatica, DataStage) to Spark or cloud-based data platforms
- Understanding of data pipeline re-engineering, re-platforming, and performance optimization strategies
Domain Knowledge
- Experience working with customer or financial data domains is an asset
Experience in financial services or regulated environments is preferred
Nice-to-Have Skills
- Experience with cloud data platforms (Azure, AWS, or GCP)
- Familiarity with data orchestration tools (Airflow or similar)
- Exposure to real-time/streaming data processing (Spark Streaming, Kafka Streams)
- Knowledge of data governance, lineage, and metadata management
- Experience in data quality frameworks and reconciliation methodologies
- Exposure to event-driven data architectures
Location
Toronto, Ontario, Canada
#J-18808-Ljbffr
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
