Data Engineer
- Toronto, ON, M5H 1H1, Canada
Applications open in a new tab.
Job details
- Apply by
- Experience
- 3–5 years of experience in data engineering
- Posting language
- English
- Posted
Original job description
Requisition ID: 277426
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
The Role
Contributes to the overall success of GFT and Finance Data Platform (FRDP) by designing, building, and owning scalable and reliable data pipelines. Ensures delivery of high-quality data solutions aligned to enterprise standards while supporting regulatory, audit, and operational requirements.
What will we expect from you?
1. End-to-End Data Pipeline Ownership
- Design, develop, and own ingestion, transformation, and publishing pipelines across FRDP
- Build scalable data workflows across structured, semi-structured, and unstructured datasets
- Ensure pipelines are optimized for performance, scalability, and reliability.
2. Data Modeling & Engineering Design
- Design data models aligned with business and analytical requirements
- Develop transformation logic using SQL and distributed processing frameworks such as Spark
3. Data Quality, Governance & Compliance
- Implement and enforce data quality frameworks and validation rules
- Ensure compliance with data governance, lineage, audit, and regulatory requirements (e.g., RDARR, SOX)
- Participate in defining data standards and best practices.
4. Production Reliability & Operational Excellence
- Own production pipelines and ensure SLA adherence
- Lead root-cause analysis and resolve production incidents
- Enhance observability, monitoring, and alerting across pipelines
5. Cross-Team Integration & Delivery
- Collaborate with upstream and downstream teams to integrate data systems
- Translate business requirements into scalable technical solutions
- Support onboarding of complex data sources and consumers.
6. Continuous Improvement & Engineering Practices
- Drive improvements in pipeline efficiency, maintainability, and reuse
- Contribute to standardization of frameworks and development practices
- Mentor junior engineers (Level 6)
What You Will Bring to Succeed
- 3–5 years of experience in data engineering
- Strong expertise in SQL, data modeling, and data pipeline development
- Experience working in enterprise-scale data platforms and in Cloud (Google/Azure)
- Proven experience owning production data pipelines
Technical Skills
- Data Processing: Advanced SQL, Python, Spark
- Ingestion: NiFi (design and optimization)
- Storage: Object Storage (partitioning, performance optimization), RDBMS
- Query Engine: Trino (query optimization, federation)
- Orchestration: Autosys/Cloud Composer
- Data Quality: Implementation of DQ frameworks
- Visualization: Power BI
The Workplace
- We are technology partners who help the business transform how our employees around the world work
- We have an inclusive and collaborative working environment that encourages creativity, curiosity, and celebrates success!
- You'll get to work with and learn from diverse industry leaders, who have hailed from top technology companies around the world
- We foster an environment of innovation and continuous learning
- We care about our people, allowing them to design how they work to deliver amazing results
- We offer a competitive total rewards package, including a performance bonus, company matching programs (on pension & profit sharing), and generous vacation
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.
More about this job
Responsibilities
The role involves designing, building, and owning scalable data pipelines while ensuring high-quality data solutions that meet regulatory and operational standards. You will also collaborate with cross-functional teams to integrate data systems and drive continuous improvements in engineering practices.
Requirements
Candidates must have 3–5 years of experience in data engineering with strong expertise in SQL, data modeling, and distributed processing frameworks. Proven experience in owning production data pipelines and working within enterprise-scale cloud environments is required.
Skills
- SQL
- Python
- Spark
- Data modeling
- Data pipeline development
- NiFi
- Object storage
- RDBMS
- Trino
- Autosys
- Cloud Composer
- Data quality frameworks
- Power BI
- Cloud platforms
- Distributed processing
Benefits
- Performance bonus
- Company matching programs
- Pension matching
- Profit sharing
- Generous vacation
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
- Engineering
Keywords
- Data Engineering
- SQL
- Python
- Spark
- NiFi
- Trino
- Autosys
- Cloud Composer
- Power BI
- Data Modeling
- Data Pipelines
- Data Governance
- RDARR
- SOX
- Cloud
- Google Cloud
- Azure
- Distributed Processing
- Data Quality
- Observability
- Monitoring
- Alerting
- Finance Data Platform
- ETL
- Data Ingestion
- Data Transformation
- Production Reliability
- SLA
- Root-cause analysis
- Engineering Practices