Software Engineer, Data Platform

Jobgether; Toronto; Hybrid; CAD 130,000 - 165,000; Full time

Benefits offered by this job

Remote work (Toronto remote)

Competitive CAD salary

Comprehensive medical benefits

Career growth and technical learning

Work on large-scale data systems

Job summary

Jobgether is seeking a Software Engineer, Data Platform in Canada to help build scalable data ingestion pipelines, backend services, and storage systems for transactional, analytical, and ML workloads.

You will modernize legacy data infrastructure while collaborating with analytics, ML, and infra teams to establish reliable data foundations and governance across products and services.

Qualifications

• Strong understanding of data governance, data lifecycle management, and compliance.
• Experience with OLAP/OLTP databases and selecting appropriate technologies.
• Hands-on with production-scale data warehouse tech (Databricks, ClickHouse, Redshift).
• Proficient in SQL, data modeling, and performance tuning.
• Experience with cloud platforms (AWS, GCP); multi-cloud experience a plus.
• Familiarity with Infra-as-Code tools (Terraform, CloudFormation).
• Strong communication, collaboration, and documentation skills.

Responsibilities

• Design, develop, and deliver scalable data ingestion pipelines and infrastructure.
• Migrate legacy data lifecycle systems to modern platform architectures with minimal disruption.
• Establish SLIs/SLOs with dashboards, monitoring, and alerting.
• Build data storage supporting transactional, analytical, and ML workloads.
• Implement monitoring, observability, and incident response for data pipelines.
• Collaborate with engineering, analytics, ML, and infra teams to define data contracts and standards.
• Architect semantic metadata layer for data discovery and governance.
• Deliver multi-tenant data models enabling secure data sharing with regulatory compliance.
• Contribute to architectural decisions, specifications, and long-term platform strategy.
• Interface legacy platforms with modern architectures and scalable integration patterns.

Skills

SQL skills

Data governance

Cloud platforms

Communication & collaboration

Learning new technologies

Big-picture problem solving

Tools

Databricks

ClickHouse

Redshift

Airflow

Kafka

Apache Flink

Docker

Kubernetes

Terraform

CloudFormation

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Data Platform based in Canada.

This role sits at the heart of a modern data platform responsible for moving, processing, and exposing large volumes of data.

You’ll help build scalable ingestion pipelines, backend services, and storage systems supporting transactional, analytical, and machine learning workloads.

The position combines new platform development with the modernization of legacy data infrastructure.

You’ll work closely with engineering, analytics, machine learning, and infrastructure teams to establish reliable and governed data foundations.

Your work will influence how data is discovered, shared, secured, and reused across products and services.

You’ll operate in a technically complex environment where reliability, observability, scalability, and regulatory compliance are key priorities.

This is an opportunity to solve large-scale data challenges while directly contributing to the evolution of a growing technology platform.

Accountabilities

• Support the design, development, and delivery of scalable data ingestion pipelines and supporting infrastructure.
• Help migrate legacy data lifecycle management systems to modern platform architectures while minimizing disruption to existing data consumers.
• Establish and maintain Service Level Indicators (SLIs) and Service Level Objectives (SLOs), supported by dashboards, monitoring, and alerting.
• Build flexible data storage capabilities that support transactional, analytical, and machine learning workloads.
• Implement comprehensive monitoring, observability, and incident-response practices across event-driven data pipelines and services.
• Collaborate with product engineering, analytics, and machine learning teams to define data contracts, functional requirements, technical standards, and platform capabilities.
• Design and implement a semantic metadata layer that classifies and labels data assets, improving discovery, access policies, and opportunities for cross-product data reuse.
• Architect and deliver multi-tenant data models that enable secure data sharing and isolation across clients while supporting regulatory and government compliance requirements.
• Contribute to architectural decisions, technical specifications, system design discussions, and long-term platform strategy.
• Help connect legacy platforms with modern architectures through robust interfaces, migration strategies, and scalable integration patterns.
• Apply infrastructure-as-code, cloud-native, containerization, and orchestration practices to build reliable and maintainable data systems.

Requirements

• Demonstrated ability to learn new technologies, frameworks, and technical domains quickly.
• Product-oriented mindset with an ability to solve complex, big-picture problems while considering end-user needs.
• Strong understanding of data governance and data lifecycle management, including data quality, lineage, retention, access control, and compliance.
• Strong knowledge of database technologies and the differences between OLAP and OLTP workloads, with the ability to select appropriate technologies for different use cases.
• Hands-on experience operating production-scale data warehouse technologies such as Databricks, ClickHouse, Redshift, or comparable platforms.
• Strong SQL skills, including the ability to write, analyze, and optimize complex queries.
• Experience designing complex systems and identifying reusable primitives that can support evolving business requirements and future roadmaps.
• Experience designing and operating data systems on major cloud platforms, particularly AWS or GCP, ideally within multi-cloud environments.
• Proficiency with containerization and orchestration technologies such as Docker and Kubernetes.
• Proven experience integrating legacy systems with modern architectures through well-designed interfaces and structured migration strategies.
• Experience with Infrastructure-as-Code tools such as Terraform, CloudFormation, or similar technologies.
• Strong communication and collaboration skills, with the ability to facilitate architecture discussions, document technical decisions, write specifications, and work effectively across engineering teams.
• Familiarity with Elixir for concurrent and fault-tolerant data services is an asset.
• Experience with data pipeline and streaming technologies such as Airflow, Kafka, Apache Flink, or similar is an asset.
• Hands-on experience with columnar and OLAP databases such as Databricks or ClickHouse is an asset.
• Additional GCP experience is an advantage for candidates with a strong AWS background.
• Candidates who do not meet every listed qualification but demonstrate strong technical potential and relevant experience are encouraged to apply.

Benefits

• Base salary: CAD $130,000–$165,000 annually.
• Potential additional bonus depending on the position ultimately offered.
• Comprehensive medical, financial, and other employee benefits.
• Remote work opportunity based in Toronto, Canada.
• Opportunity to work on large-scale data infrastructure and modern cloud technologies.
• Exposure to distributed systems, data governance, machine learning workloads, and multi-tenant architectures.
• Opportunity to influence the modernization of legacy systems and the evolution of a unified data platform.
• Collaborative environment working across engineering, analytics, machine learning, infrastructure, and product teams.
• Inclusive workplace committed to diversity, equal opportunity, and supporting employees from varied backgrounds.
• Strong emphasis on technical growth, learning, and solving complex engineering challenges.