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Job Overview
Location
Toronto, Ontario
Job Type
Full-time
Category
Software Engineering
Date Posted
October 15, 2025
Full Job Description
đź“‹ Description
- • Architect and own end-to-end, cloud-native ELT pipelines that power analytics for investment-research workflows used by global banks and asset managers. You will design scalable ingestion from internal micro-services and external data vendors, then transform raw data into analytics-ready models inside Snowflake using dbt.
- • Build both batch and real-time ingestion jobs that land data in AWS S3, trigger Glue/Lambda processes, and stream into Snowflake via Snowpipe. You will tune file formats, partitioning, and clustering strategies to keep petabyte-scale queries sub-second.
- • Model clean, version-controlled dbt projects with modular layers (staging, marts, metrics) that enforce naming conventions, documentation, and testing. Implement incremental models, snapshots, and advanced materializations to reduce cost and latency.
- • Embed data-quality gates at every step: dbt tests, Great Expectations suites, anomaly detection, and lineage graphs. You will define SLAs, set up Monte Carlo or similar observability alerts, and run root-cause drills before stakeholders notice an issue.
- • Partner with DevOps to automate CI/CD for dbt, Terraform the Snowflake and AWS resources, and monitor pipeline health in Airflow or Dagster. You will write Python utilities that auto-heal failed tasks and publish metrics to Datadog dashboards.
- • Create self-service tooling—CLI generators, dbt docs sites, and lightweight APIs—that let analysts spin up curated datasets without tickets. Your work will shrink time-to-insight from days to minutes.
- • Continuously optimize: rewrite slow SQL, leverage Snowflake’s query acceleration, right-size warehouses, and implement cost-allocation tags. You will present monthly savings reports to leadership.
- • Contribute to cloud-migration playbooks as we retire legacy SQL Server warehouses. You will reverse-engineer old ETL, map business logic, and run parallel validation to guarantee zero-downtime cutover.
- • Champion data culture through lunch-and-learns, code reviews, and guild meetings. You will mentor junior engineers and set the technical bar for the next wave of hires.
🎯 Requirements
- • 3–6 years of hands-on data-engineering experience in AWS, Snowflake, and dbt
- • Expert-level SQL and production-grade Python for data manipulation and automation
- • Proven track record designing ELT pipelines, data-warehouse schemas, and performance tuning at scale
- • Experience with workflow orchestration tools such as Airflow or Dagster
- • Familiarity with infrastructure-as-code (Terraform or CloudFormation) and CI/CD best practices
- • Nice-to-have: exposure to data observability tools (Great Expectations, Monte Carlo) and prior involvement in legacy-to-modern data-stack migrations
🏖️ Benefits
- • Competitive compensation benchmarked to Toronto market, reviewed annually
- • Comprehensive health-care plan including medical, dental, and vision coverage
- • Generous vacation and personal-day policy plus company-wide recharge weeks
- • Generous referral program with cash bonuses for successful hires
Skills & Technologies
About Blue Matrix LLC
Blue Matrix LLC provides cloud-based financial research and publishing software to investment banks, asset managers, research boutiques, and corporations. Its platform streamlines the creation, editing, distribution, and compliance of equity and fixed-income research, corporate access events, and investor communications. Services include real-time collaboration, document management, analytics, and regulatory workflow tools that integrate with third-party data feeds and CRM systems. Headquartered in New York with offices in London and Hong Kong, the company serves global clients seeking secure, scalable solutions for research production and distribution across North America, Europe, and Asia-Pacific.
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