Analytics Engineer, Global Analytics Engineering

Scotiabank • Toronto, ON

3d • Onsite

About The Position

We are seeking a skilled and enthusiastic Data Engineer to join our team and contribute to designing and delivering scalable, high‑quality data products. In this role, you will take ownership of transforming raw data into well‑modeled, trusted, and analytics‑ready datasets that power decision‑making across the organization. You will work with modern data engineering tools, cloud technologies, and cross‑functional teams to build robust, efficient, and maintainable data solutions.

Requirements

• Bachelor's degree in Computer Science, Analytics, or related field.
• Strong proficiency in SQL with experience working with relational or analytical databases.
• Hands-on experience with dbt for data modeling, testing, and transformation.
• Practical experience with Google Cloud Platform (BigQuery, Cloud Storage, Cloud Composer) or equivalent cloud platforms.
• Solid understanding of data warehousing concepts, ETL/ELT patterns, and analytical data modeling.
• Proficiency with Git and version control workflows.
• Strong problem-solving skills, attention to detail, and the ability to work collaboratively in a fast-paced environment.

Nice To Haves

• Experience with Python for automation, tooling, and workflow development.
• Familiarity with data observability tools, CI/CD pipelines, or infrastructure-as-code concepts.
• Experience with data quality frameworks (e.g., dbt tests).
• Exposure to BI tools (e.g., Looker, Tableau, Power BI).

Responsibilities

• Design, build, and maintain production-grade data models and transformation layers using dbt (Data Build Tool).
• Develop, optimize, and orchestrate ETL/ELT workflows using Google Cloud Platform (GCP) services such as BigQuery, Cloud Storage, and Cloud Composer.
• Partner closely with data analysts, data engineers, and business stakeholders to ensure data accuracy, reliability, and usability.
• Establish and enforce best practices for version control, testing, documentation, deployment, and data governance.
• Monitor, detect, and troubleshoot issues across the data ecosystem to ensure high availability and performance.
• Contribute to architectural decisions that shape the evolution of modern data stacks and broader data strategy.
• Drive continuous improvement by identifying automation opportunities, optimizing performance, and enhancing data pipelines.

Benefits

• Build high‑impact data models that streamline analytics, and reporting.
• Contribute to a scalable and efficient modern data stack centered on GCP and dbt.
• Help shape and evolve data engineering standards, best practices, and development processes.
• Work with experienced analytics engineers and data leaders who support your growth and career development.
• Influence critical business decisions by delivering reliable, well‑structured, and trusted data.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level