Source-listed Job

Senior Software Development Engineer

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

Job Remote Source description available
Jobgether Source published Oct 20, 2026 Source retrieved Oct 20, 2026
Source: jobgether (lever) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
Description from the source The source description is formatted below for discovery. The provider owns the original wording and may change its requirements or close applications.
EmploymentFull-time
Work modeRemote / location-flexible

Overview

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

Full 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 Senior Software Development Engineer based in Canada. The Senior Software Development Engineer will help shape an enterprise data platform that empowers engineering, analytics, and business teams to access, understand, and use trusted data independently. This remote role focuses on designing scalable data products, robust data architectures, and intuitive self-service experiences that reduce manual work and accelerate decision-making. The successful candidate will combine strong Python development and AWS expertise with data modeling, platform engineering, and API design to build reusable solutions for diverse internal users. They will also contribute to AI-assisted automation and enterprise data context, making information more discoverable and useful for both people and AI agents. Working across distributed teams and time zones, they will own technical outcomes from understanding user needs to delivering reliable production services. This is an opportunity for a hands-on engineer to influence platform strategy, improve operational efficiency, and advance modern data engineering practices.

Design scalable data products: Develop data models and domain-driven components that transform raw data into reusable, well-governed data products for downstream consumers. Build enterprise data context: Contribute to semantic models, ontologies, knowledge bases, and related capabilities that improve data discovery, understanding, and usability for people and AI agents. Develop self-service platform experiences: Build end-to-end tools and workflows for data producers and consumers, including onboarding processes, SQL automation, data quality monitoring, APIs, and data product access mechanisms. Implement AI-assisted automation: Design and evolve AI-enabled and agentic workflows that reduce manual effort across platform operations, including migrations, impact assessments, and guided processes for engineering and data teams. Ensure service reliability: Lead incident response for owned services, conduct root-cause analyses and post-incident reviews, implement durable fixes, and create runbooks that enable first-line support teams to resolve recurring issues independently. Drive platform UX priorities: Collaborate with engineering leadership and distributed teams across the United States and India to translate user needs into prioritized backlogs, evaluate trade-offs, remove blockers, and take ownership of delivery outcomes. Develop reusable platform patterns: Create modular frameworks, plugins, and scalable automation capabilities that can be adopted consistently across multiple teams. Improve data governance and quality: Support reliable, secure, and accessible data experiences through appropriate data quality practices, governance controls, and access management. Collaborate across functions: Partner with engineers, analysts, platform teams, and other stakeholders to understand requirements, deliver solutions, and continuously improve the enterprise data platform. Requirements: Professional experience: At least 7 years of experience in data engineering, data platform engineering, or software engineering. Python development: At least 5 years of professional Python experience, including building APIs, automation solutions, and data or platform tooling, with the ability to troubleshoot distributed data systems. Data modeling and architecture: Strong knowledge of data modeling, data architecture, domain-driven design, and the development of reusable data products for downstream consumers. Self-service platform engineering: Experience building APIs, workflows, or tools that allow data producers and consumers to work independently without relying on manual support. Reusable system design: Proven ability to design modular and extensible platform patterns, such as frameworks, plugins, or marketplaces, that scale automation across multiple teams. AWS expertise: Hands-on experience with AWS services, including S3, Lambda, Glue, Lake Formation, Redshift, and API Gateway. Modern data architectures: Production experience with lakehouse architectures and Apache Iceberg, along with orchestration using Apache Airflow. Problem-solving and operational ownership: Ability to diagnose complex technical issues, lead root-cause investigations, implement lasting solutions, and maintain reliable production services. Cross-functional collaboration: Strong communication and prioritization skills, with the ability to work effectively with distributed teams, understand user requirements, manage technical trade-offs, and deliver results independently. Preferred AI and data context experience: Production experience developing AI-assisted or agentic workflows for analytics, migration, or platform enablement. Familiarity with semantic layers, ontologies, knowledge graphs, or enterprise knowledge bases is an advantage. Preferred governance experience: Knowledge of data quality frameworks, data governance, and access management practices. Learning mindset: Candidates are encouraged to apply even if they do not meet every requirement, as transferable skills, diverse backgrounds, and a willingness to learn are valued. Benefits: Competitive annual salary: CAD $128,500–$192,500, depending on relevant skills, experience, and geographic location. Potential performance bonus: Eligibility for a discretionary cash bonus scheme targeting 15% of base salary, based on individual and company performance. Potential equity participation: The role may be eligible for an employee equity plan. Remote work flexibility: Work remotely from home in Canada, with occasional office visits potentially required for team meetings or events. Healthcare coverage: Benefits include health, dental, and vision insurance. Financial protection: Life insurance, critical illness coverage, and accidental death and dismemberment (AD&D) insurance. Health and wellness support: Healthcare spending account, employee assistance program, and paid wellness days. Time off: Paid sick time, paid personal time, paid holidays, and generous time-off provisions. Family support: Paid parental leave. Retirement and savings: Retirement savings program and employee stock purchase plan. Additional benefits: Other benefits may be available according to applicable benefit plans, local requirements, and employment location.

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