Senior Engineer, Data Platform

<img src="https://app.gurulink.ca/img/gl_logo_112x112.jpg" border="0"><br><br><b>Location:</b> REMOTE / Toronto, Ontario - Canada<br><b>Job Type:</b> Permanent<br><br><b>Description:</b><p>We&#8217;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.<br><br>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&#8217;ll work across data ingestion, storage architecture, reliability, observability, governance, and platform modernization while supporting transactional, analytical, and machine learning workloads.<br><br>The ideal candidate combines strong backend and data platform engineering fundamentals with experience designing and operating complex production data systems at scale.<br><br>What You&#8217;ll Do<br><br>- Design, build, and operate scalable data ingestion pipelines and the infrastructure supporting them.<br>- Develop backend services and platform capabilities that enable data to be reliably accessed across multiple products and engineering teams.<br>- Help migrate legacy data lifecycle management and ingestion systems onto modern platform architecture without disrupting existing data consumers.<br>- Design flexible data storage architecture capable of supporting transactional, analytical, and machine learning workloads.<br>- Establish SLIs and SLOs for data platform services and build the monitoring, dashboards, and alerting required to track reliability and performance.<br>- Implement observability and incident response practices across event data pipelines and supporting services.<br>- Work closely with product engineering, analytics, infrastructure, and machine learning teams to establish data contracts, functional requirements, and platform standards.<br>- Design metadata and semantic layers that improve how data assets are classified, discovered, governed, and reused across products.<br>- Help architect multi-tenant data models that provide appropriate data isolation, secure sharing, access controls, and support for compliance requirements.<br>- Contribute to the technical direction of the data platform and help establish architectural patterns that can evolve alongside future product and business requirements.<br><br>The Opportunity<br><br>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.<br><br>You&#8217;ll be working on problems that go beyond building individual pipelines&#8212;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.</p><br><b>Must Have skills:</b><p>What We&#8217;re Looking For<br><br>- Strong experience designing and operating production data platforms, ingestion systems, backend services, or other large-scale data infrastructure.<br>- Deep understanding of data governance and lifecycle management, including data quality, lineage, retention, access control, and data discovery.<br>- Strong understanding of database architecture and when to apply OLTP versus OLAP technologies.<br>- Production experience with data warehouse or columnar database technologies such as Databricks, ClickHouse, Redshift, or similar platforms.<br>- Strong SQL skills with the ability to write, troubleshoot, and optimize queries.<br>- Experience designing complex systems and identifying reusable architectural primitives that can support changing business and product requirements.<br>- Experience designing and operating data systems on AWS. GCP and experience working in multi-cloud environments are also relevant.<br>- Hands-on experience with Docker and Kubernetes in production environments.<br>- Experience integrating legacy systems with modern architectures through well-designed interfaces and migration strategies.<br>- Experience with Infrastructure-as-Code technologies such as Terraform, CloudFormation, or similar tools.<br>- Experience building reliable production systems with monitoring, observability, alerting, SLIs/SLOs, and incident response practices.<br>- Experience with data pipeline, streaming, or event-processing technologies such as Kafka, Apache Flink, Airflow, or similar technologies is an asset.<br>- Experience designing multi-tenant data systems with appropriate isolation, access controls, and secure data-sharing capabilities.<br>- Strong system design and technical communication skills, with the ability to lead architecture discussions, write technical specifications, document decisions, and collaborate across engineering teams.<br>- Familiarity with Elixir and experience building concurrent or fault-tolerant data services is considered an asset.<br><br>The base pay range for this position is $145,000-$185,000/year CAD</p><br><b>Job Function:</b> Backend engineer, data platform engineer<br><br><br>

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