Senior Engineer, Data Platform

Location: REMOTE / Toronto, Ontario
This job allows you to work remotely.

We're working with an established technology company that is expanding its Data Platform team and looking for a Senior Engineer to help design, build, and evolve the systems responsible for how large volumes of data are ingested, processed, stored, governed, and exposed across its products.
This is a hands-on senior engineering role focused on building scalable data infrastructure and backend services, modernizing legacy data pipelines, and developing a more unified approach to how data is accessed across the organization. You'll work across data ingestion, storage architecture, reliability, observability, governance, and platform modernization while supporting transactional, analytical, and machine learning workloads.
The ideal candidate combines strong backend and data platform engineering fundamentals with experience designing and operating complex production data systems at scale.
What You'll Do
- Design, build, and operate scalable data ingestion pipelines and the infrastructure supporting them.
- Develop backend services and platform capabilities that enable data to be reliably accessed across multiple products and engineering teams.
- Help migrate legacy data lifecycle management and ingestion systems onto modern platform architecture without disrupting existing data consumers.
- Design flexible data storage architecture capable of supporting transactional, analytical, and machine learning workloads.
- Establish SLIs and SLOs for data platform services and build the monitoring, dashboards, and alerting required to track reliability and performance.
- Implement observability and incident response practices across event data pipelines and supporting services.
- Work closely with product engineering, analytics, infrastructure, and machine learning teams to establish data contracts, functional requirements, and platform standards.
- Design metadata and semantic layers that improve how data assets are classified, discovered, governed, and reused across products.
- Help architect multi-tenant data models that provide appropriate data isolation, secure sharing, access controls, and support for compliance requirements.
- Contribute to the technical direction of the data platform and help establish architectural patterns that can evolve alongside future product and business requirements.
The Opportunity
This is a strong opportunity for an experienced backend or data platform engineer who wants to work on the foundational systems responsible for moving and managing data across a large-scale production environment.
You'll be working on problems that go beyond building individual pipelines—the broader challenge involves platform architecture, data storage, reliability, governance, multi-tenancy, and safely evolving legacy systems into a more modern and unified data platform.

Must Have Skills:
What We're Looking For
- Strong experience designing and operating production data platforms, ingestion systems, backend services, or other large-scale data infrastructure.
- Deep understanding of data governance and lifecycle management, including data quality, lineage, retention, access control, and data discovery.
- Strong understanding of database architecture and when to apply OLTP versus OLAP technologies.
- Production experience with data warehouse or columnar database technologies such as Databricks, ClickHouse, Redshift, or similar platforms.
- Strong SQL skills with the ability to write, troubleshoot, and optimize queries.
- Experience designing complex systems and identifying reusable architectural primitives that can support changing business and product requirements.
- Experience designing and operating data systems on AWS. GCP and experience working in multi-cloud environments are also relevant.
- Hands-on experience with Docker and Kubernetes in production environments.
- Experience integrating legacy systems with modern architectures through well-designed interfaces and migration strategies.
- Experience with Infrastructure-as-Code technologies such as Terraform, CloudFormation, or similar tools.
- Experience building reliable production systems with monitoring, observability, alerting, SLIs/SLOs, and incident response practices.
- Experience with data pipeline, streaming, or event-processing technologies such as Kafka, Apache Flink, Airflow, or similar technologies is an asset.
- Experience designing multi-tenant data systems with appropriate isolation, access controls, and secure data-sharing capabilities.
- Strong system design and technical communication skills, with the ability to lead architecture discussions, write technical specifications, document decisions, and collaborate across engineering teams.
- Familiarity with Elixir and experience building concurrent or fault-tolerant data services is considered an asset.