appdirect
Data Platform Engineer
At a Glance
- Location
- Montreal, Canada
- Experience
- 5+ years
- Posted
- 2026-07-20T03:18:25-04:00
Key Requirements
Required Skills
Domain Knowledge
- Automation
Requirements
Strong understanding of AI-assisted development workflows, with proven hands-on experience using tools such as Cursor, Claude, to improve efficiency, automation, and code quality.
5+ years of hands-on experience running and operating MySQL and/or PostgreSQL in large-scale production environments, with deep knowledge of database internals
2+ years of hands-on experience with NoSQL—one of MongoDB, Redis, or Elasticsearch.
2+ years of experience with AWS cloud services.
Strong expertise in Infrastructure as Code (IaC), with a primary focus on Terraform.
Strong preferred exposure to lakehouse and analytics infrastructure (e.g., Databricks, Apache Iceberg, Unity Catalog) with an interest in collaborating with Data Insights on lakehouse enablement.
Responsibilities
Lead large-scale database migration projects driven by company acquisitions, client onboarding, and platform growth—planning for minimal downtime, strong rollback strategies, and zero data loss.
Design and execute deployment strategies for blue/green rollouts, data archiving, and partitioning across relational, key-value, and document data stores.
Use AI-powered automation to strengthen our data platform across our quality pillars: operational excellence, security and compliance, performance and scalability, and resiliency and capacity planning.
Apply AI-assisted development tools and spec-driven workflows to design, automate, and ship database platform changes faster—Terraform modules, runbooks, diagnostics, and operational tooling—with clear acceptance criteria and high code quality.
Partner with the Data Insights team on lakehouse enablement (e.g., Databricks, Apache Iceberg, Unity Catalog)—bridging transactional data stores and analytics infrastructure through reliable access patterns, security/governance alignment, and safe onboarding of workloads onto the lakehouse.
Guide engineers in delivering fit-for-purpose database solutions across relational (MySQL, PostgreSQL, SQL Server), key-value (Redis), document (MongoDB), and search (Elasticsearch).