Senior Data Engineer with Cloud

Scotiabank•Toronto, ON

84d•Onsite

About The Position

The Global Risk and Treasury Technology team provides development and support services for Group Treasury (including Structural Interest Rate Risk management, Asset/Liability Management, Funds Transfer Pricing, Liquidity Risk, Stress Testing) and Global Risk Management (Global Retail/Corporate/Commercial Credit Risk, Counterparty Credit Risk, Operational/Non-Operational Risk Management). The Senior Data Engineer is responsible for developing and implementing technical solutions to support the Group Treasury business with a focus on Data Engineering building reusable data assets for the group and the bank. You will be required to participate in multiple projects, including technical design, use cases, and process workflow of complex business processes for internal clients. You must possess the ability to work with a team of technology focused peers and the ability to juggle multiple/concurrent tasks. You must thrive on challenge, be proactive, dynamic and demonstrate initiative and eagerness to learn.

Requirements

Bachelor's degree in a technical field such as Computer science, Information Systems, Computer engineering, Data Science or related field required.
5+ years of experience in data engineering, with hands-on experience in Microsoft Azure and GCP data tools.
Strong proficiency in SQL Server, T-SQL, SSIS, and Azure Data Factory.
Experience with BigQuery, Cloud Storage, and Dataflow or Apache Beam.
Solid understanding of financial data domains such as general ledger, cash management, liquidity, regulatory reporting, and risk analytics.
Experience working in or with financial institutions, banks, or treasury departments.
Familiarity with CI/CD tools (e.g., Azure DevOps, GitHub Actions, Cloud Build) and infrastructure-as-code (e.g., Terraform).
Excellent problem solving and analytical skills and be capable of multi-tasking and managing concurrent tasks and initiatives.
Ability to solve technical problems/ processes and understand complex details.
A high level of interpersonal and verbal communication skills necessary to relate to other people at their systems knowledge level.
Self motivated and curious to learn new technologies and business use cases.

Nice To Haves

Experience with Databricks, Delta Lake, MLflow, and Apache Airflow.
Knowledge of Power BI, Looker, or other visualization tools.
Certifications such as Azure Data Engineer Associate or Google Professional Data Engineer.
Experience with financial compliance standards (e.g., SOX, Basel, IFRS).
Experience working in Agile/Scrum environments.

Responsibilities

Design, develop, and optimize ETL/ELT pipelines using Azure Data Factory, SQL Server Integration Services (SSIS), and BigQuery.
Build and maintain data workflows across Azure Synapse Analytics, Azure Data Lake, and GCP BigQuery, integrating structured and semi-structured financial data sources.
Lead modernization of legacy financial data systems to cloud-native architectures on Azure and GCP.
Develop scalable data models and transformation logic to support finance, treasury, and regulatory reporting.
Implement data governance, lineage, and quality frameworks across multi-cloud environments.
Collaborate with finance, treasury, and risk teams to understand data requirements and translate them into technical solutions.
Ensure compliance with financial data standards, including auditability, traceability, and regulatory controls.
Mentor junior engineers and promote best practices in data engineering, DevOps, and CI/CD.