Opens an external site
- Employment type
- Full-time
- Experience level
- Lead · 10+ years
- Minimum education
- Bachelor’s degree
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Canada
Job summary
The Senior Staff Data Platform Engineer will lead the design and execution of the technical strategy for the data platform while working hands-on to build scalable, governed systems. This role involves bridging the gap between architectural vision and production-grade engineering to empower domain teams to manage their own data pipelines.
Job details
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.
What you’ll do
The Senior Staff Data Platform Engineer will lead the design and execution of the technical strategy for the data platform while working hands-on to build scalable, governed systems. This role involves bridging the gap between architectural vision and production-grade engineering to empower domain teams to manage their own data pipelines.
Requirements
Candidates must have 8+ years of scalable development experience with a strong background in data engineering and platform modernization. A degree in Computer Science or equivalent professional experience is required, along with deep expertise in AWS, streaming technologies, and medallion architecture.
Benefits
- Flexible hybrid work environment
- Employee resource groups
- Professional development opportunities
- Inclusive culture
Listed skills
- CI/CD · Preferred
- AI-assisted development · Preferred
- Amazon Web Services · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data engineering
- Data platform architecture
- AWS
- Apache Iceberg
- dbt
- Data governance
- Streaming pipelines
- Data modeling
- Metadata management
- DataHub
- Software design
- Technical leadership
- Cloud-native infrastructure
- CI/CD
- Infrastructure-as-Code
- AI-assisted development
- Scalability Design
- DataHub (Software)
- Technical Strategy
- Continuous Development
- DevSecOps
- Cloud-Native Computing
- Pipelines
- Solution Design
- Organizational Strategy
- Cloud-Native Infrastructure
- Observability
- Workflow Management
- Apache Airflow
- AWS Glue
- Technical Leadership
- Infrastructure as Code (IaC)
- Planning
- Abstractions
- Agile Methodology
- Artificial Intelligence
- Amazon Web Services
- Test Automation
- Microsoft Azure
- Google BigQuery
- Business Requirements
- Communication
- Computer Science
- Computer Engineering
- Continuous Improvement Process
- Data Engineering
- Data Quality
- Design Leadership
- Equities
- Event-Driven Programming
Job areas
- Technology
- Data & Analytics
- Software
- Engineering
- Management & Leadership
- Data Platform Engineer
- Platform Engineer
- Software and Applications Developers and Analysts Not Elsewhere Classified
- Validation Engineers
- Industrial Engineers
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