Senior Data Engineer

Toronto, ON
On-site
Posted Nov 10, 2026
1 position

Opens LinkedIn

Employment type: Full-time
Experience level: Senior
Posting language: English
Application method: Apply on LinkedIn (LinkedIn sign-in required)

Job summary

Analyze and onboard datasets, then design, build, and operate scalable AWS data pipelines and data products for Middle Office functions. Develop orchestration, data models, CI/CD, and infrastructure automation, while troubleshooting production issues and improving reliability.

Job details

Project Description: We are looking for an experienced Senior Data Engineer to support the onboarding, integration, and operationalization of datasets used by Middle Office functions. The role focuses on building scalable, production-grade data pipelines and data products on AWS, enabling reliable data delivery for analytics, reporting, and downstream applications. The successful candidate will own the full lifecycle from source analysis and solution design through implementation, deployment, and operational support. The role is for subcontractors. Responsibilities: - Data Onboarding & Integration: Analyze source systems, onboard new datasets, and design scalable ingestion and transformation pipelines to support Middle Office business needs. - Data Engineering: Develop and maintain production-grade pipelines using AWS services including EMR, Glue, Athena, and S3, leveraging Spark/PySpark and modern data lake technologies. - Workflow Automation: Build and manage orchestration workflows using Airflow or equivalent platforms, including scheduling, monitoring, alerting, and recovery processes. - Data Architecture & Modeling: Design scalable data models, schema structures, partitioning strategies, and data quality controls to ensure reliable and efficient data consumption. - DevOps & Operational Excellence: Implement CI/CD pipelines and infrastructure-as-code practices using Terraform and GitHub Actions, ensuring maintainable and supportable solutions. - Production Support: Troubleshoot data quality, performance, and operational issues while driving long-term reliability improvements. Mandatory Skills Description: - Strong hands-on experience building and operating AWS-based data platforms and data pipelines. - Advanced expertise with Apache Spark, PySpark, distributed data processing, and performance optimization. - Experience with modern data lake technologies, particularly Apache Hudi and Apache Iceberg. - Strong Python programming and software engineering practices, including testing, code quality, and Git-based development workflows. - Hands-on experience with Apache Airflow or comparable workflow orchestration platforms. - Experience with Terraform, CI/CD pipelines, and infrastructure automation. - Ability to independently translate business requirements into production-ready data solutions. Nice-to-Have Skills Description: We are particularly interested in candidates who have experience building data platforms within financial services, asset management, capital markets, or investment management environments. Experience supporting Middle Office, investment operations, risk, or trading-related datasets is highly desirable. Knowledge of data governance, lineage, security, and large-scale production support is also a strong advantage.

What you’ll do

Requirements

Requires strong hands-on experience with AWS data platforms, Spark/PySpark, modern data lakes, Python, workflow orchestration, Terraform, and CI/CD. Candidates must be able to independently turn business requirements into production-ready solutions; financial services or investment operations experience is highly desirable.