Requisition ID: 265190
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.
Is this role right for you? In this role, you will:
- 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)
Do you have the skills that will enable you to succeed in this role? We’d love to work with you if you have:
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
- Proven experience in enterprise ETL/data pipeline development
- Experience with data migration and modernization initiatives (legacy → distributed platforms)
- Experience with:
- Batch processing frameworks
- Data ingestion and transformation pipelines
- Messaging systems (Kafka, MQ)
- 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(s): Canada : Ontario : Toronto
Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.