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Added 23 mins ago
Commercial & 3PL Logistics Sales Representative
Tippet-Richardson Moving & Storage
Burnaby, BC
Full-time
· Strong prospecting and lead-generation skills, including cold calling, networking, and referral development.
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Project Manager
Matchtech North America
Toronto, ON · Greater Toronto Area, Canada
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Project Manager
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$18.6 USD / hour
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Added 3 hours ago
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Rogers Bank
Cornwall, ON
Full-time
Lead initiatives that modernize collections through automation, AI-enabled capabilities, and process optimization.

Benevity

Senior Staff Data Platform Engineer

Remote, Canada

Pay: $137,800 to $178,080 CAD / year
Job type: Full-time
Workplace: Remote
Experience: 8+ years of scalable development experience, with lead and software design accountabilities, including substantial time building data platforms and pipelines.
Posting language: English
Posted: Sep 25, 2026

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Original job description

Meet Benevity

Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more!

Benevity is seeking a talented Senior Staff Data Platform Engineer, who has an extensive record of hands-on data engineering and data product development experience. This role, reporting to the Director of Engineering, plays a crucial part in shaping and executing on the technical strategy across our data platform, and in building it hands-on alongside the team, raising both velocity and quality as we go.

Position Overview:

The Senior Staff Data Platform Engineer will be the technical anchor for our data platform, and will lead the design of our data democratization strategy. You will bridge the gap between architectural vision and production-grade engineering, working hands-on alongside the team. This role requires a deep understanding of designing scalable, governed systems that power our ingestion pipelines, medallion lakehouse, semantic layer and the data products serving reporting, ensuring our platform delivers measurable value to the domain teams that build on it. The ideal candidate will have a strong technical background combined with the design leadership to take teams from vision to execution.

What You’ll Do:

Hands-on technical leadership across the full data path
Design and build the platform capabilities that let domain engineering teams take data from source to reporting themselves, landing new sources and schema changes into the streaming consumption pipeline, promoting them through the medallion layers, and defining the data products that reporting consumes.
Work hands-on across the whole path: streaming and batch pipelines, transformation models, the lakehouse and catalog layer, and the semantic layer that defines the data products consumers depend on.
Lead the design and delivery of our medallion architecture on an AWS lakehouse, object storage with open table formats (S3, Apache Iceberg), cataloging and fine-grained governance (AWS Glue, Lake Formation), and transformation frameworks (dbt), while continuing to operate and evolve our current warehouse environments and planning a credible path between the two.
Make pipelines configuration and metadata driven, so that adding an attribute, a table or a new data product is a declarative change a domain developer can make safely, rather than bespoke code only our team can write.
Ensure every pipeline, dataset and data product is registered, documented and discoverable in our metadata platform (DataHub), with schema, lineage and ownership propagated automatically rather than maintained by hand.
Design the data product and semantic layer contracts that reporting depends on, versioned, tested, with explicit ownership, quality expectations and deprecation paths.
Make AI a natural extension of your engineering practice, using tools like Cursor in spec-driven, agentic workflows, and build the internal, AI-assisted developer tooling that helps domain teams scaffold pipeline configuration, models, contracts, tests and documentation from a specification, with quality and governance enforced automatically in CI rather than through review queues.
Work with Principal Architects to lead the technical direction of our organizational strategy through implementing robust, extendable, and reusable architecture patterns.
Collaborate with product managers, staff developers, and other stakeholders to translate business requirements into technical specifications and data product designs.
Ensure security best practice across the technology stack using cloud native solution design.
Create and maintain technical documentation, architecture decisions and implementation processes, and ideate and deliver Proof of Concepts to advance our technical and product direction.
Provide mentorship and guidance to other developers on the team, encouraging continuous learning and professional development, fostering a collaborative and inclusive team environment.
Actively participate in architectural reviews to ensure quality, consistency and adherence to the north star architecture.

What You’ll Bring:

Degree in Computer Science, Computer Engineering or equivalent professional experience
8+ years of scalable development experience, with lead and software design accountabilities, including substantial time building data platforms and pipelines.
2+ years in a technical leadership role on building scalable platforms, technology transformation and modernization initiatives.
Excellent communication skills, balancing product and technical needs to deliver the best outcomes.
Solid software design fundamentals
Experience with domain driven design, loosely coupled systems, and event-driven, decoupled services
A track record of building reusable abstractions and frameworks that other engineers can build on, with the judgement to know when not to over-engineer, and comfort working through ambiguous, abstract problems
Comfort with abstract problem-solving and ambiguous challenges
Deep, hands-on data engineering experience across streaming and batch
Stream processing and event streaming platforms (Debezium, Kafka, Flink), including schema evolution and delivery-guarantee trade-offs
Lakehouse and medallion architecture on open table formats (S3, Apache Iceberg, AWS Glue, Lake Formation), plus a transformation practice with dbt
Warehouse engines at scale and declarative, asset-based orchestration (e.g. Airflow)
Experience making data discoverable, governed and trustworthy as a platform capability
Metadata, catalog and lineage platforms (DataHub, or equivalents) and metadata-as-code approaches
Data contracts and schema governance enforced automatically in CI and at runtime, not by documentation and review meetings
Data quality, observability and service levels for pipelines and data products
Experience with data products and the semantic layer
Designing and modelling a semantic layer as a governed, reusable product (Looker/LookML; familiarity with headless semantic layers such as the dbt Semantic Layer or Cube is an asset)
Defining data products with identified consumers, contracts, versioning and deprecation paths
Enough exposure to analytics and reporting delivery to understand how consumers actually use what you serve them
Cloud, delivery and AI-led engineering practice
Extensive experience with cloud-native infrastructure in AWS; working familiarity with GCP (BigQuery, Looker); Azure is a plus
Proficiency in agile, Infrastructure-as-Code, DevSecOps and automated testing, with CI/CD experience (e.g. GitHub Actions, Jenkins)
Experience with AI-led, spec-driven and agentic development workflows (e.g. Cursor), and building internal developer tooling that other engineers rely on
Proven track record of building performant, scalable and cost effective products
Commitment to continuous improvement in code, processes, and team development

Great-to-haves:

Certification in relevant cloud platforms or technologies.

Discover your purpose at work

We’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more …

Innovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose.

If the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become …

It’s time to join Benevity. We’re so excited to meet you.

Where We Work

At Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most.

Join a company where DEIB isn’t a buzzword

Diversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily - from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams.

We know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine.

That starts with a fair and accessible hiring process. If you want to feel seen, heard and celebrated, you belong at Benevity.

Candidates with disabilities who may require accommodations throughout the hiring or assessment process are encouraged to reach out to accommodations@benevity.com.

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More about this job

Responsibilities

The Senior Staff Data Platform Engineer will lead the design and execution of the technical strategy for the data platform, bridging the gap between architectural vision and production-grade engineering. This role involves hands-on development of scalable data pipelines, medallion architecture, and AI-assisted developer tooling to empower domain teams.

Requirements

Candidates must have 8+ years of scalable development experience with a strong background in data platforms and 2+ years in a technical leadership role. Proficiency in cloud-native AWS environments, streaming technologies, and modern data governance frameworks is required.

Skills

Data Engineering
Data Platform Architecture
AWS
Apache Iceberg
dbt
DataHub
Streaming Pipelines
Kafka
Flink
Data Governance
Semantic Layer
Technical Leadership
Cloud-native Infrastructure
DevSecOps
AI-assisted Development
System Design

Visa sponsorship

Not detected in the job text

Keywords

Data Platform
AWS
S3
Apache Iceberg
AWS Glue
Lake Formation
dbt
DataHub
Debezium
Kafka
Flink
Airflow
Looker
LookML
Cube
GitHub Actions
Jenkins
Cursor
Infrastructure-as-Code
DevSecOps
Medallion Architecture
Data Democratization
Domain Driven Design
Event-driven Architecture
Semantic Layer
Data Contracts
Metadata-as-code
Cloud-native
Scalable Systems
Technical Strategy

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