Benevity is hiring a Senior Staff Data Platform Engineer in Vancouver!
Benevity, a Canadian B Corporation whose software helps companies manage giving, volunteering, grantmaking and social action programs, is hiring a Senior Staff Data Platform Engineer in Vancouver. Reporting to the Director of Engineering, the role is the technical anchor for Benevity's data platform and the design lead for its data democratization strategy. The engineer will connect architectural direction with hands-on delivery, helping domain teams move data from source systems through streaming ingestion and a medallion lakehouse to reporting-ready data products. The platform spans AWS object storage with Apache Iceberg, Glue and Lake Formation governance, dbt transformations, metadata and lineage in DataHub, and a governed semantic layer. A major theme is making pipelines configuration- and metadata-driven so domain developers can safely add sources, attributes, tables and data products without bespoke platform-team code. The position also emphasizes automated contracts, quality checks and governance in CI, plus AI-assisted, spec-driven engineering workflows and internal developer tooling. The engineer will mentor developers, contribute to architecture reviews, and work with product managers, staff developers and principal architects to turn business needs into scalable, secure technical designs. Benevity describes a flexible hybrid working model with no set in-office requirement, while valuing in-person connection for onboarding, projects and team alignment.
Key responsibilities
- Provide hands-on technical leadership across ingestion, transformation, lakehouse, catalog and semantic-layer work.
- Design platform capabilities that let domain engineering teams land sources and schema changes, promote data through medallion layers, and define reporting data products.
- Lead delivery of a medallion architecture on AWS using S3, Apache Iceberg, Glue, Lake Formation and dbt while evolving existing warehouse environments.
- Make pipelines configuration- and metadata-driven so common changes are declarative and safe for domain developers.
- Ensure datasets, pipelines and data products are registered, documented and discoverable in DataHub with automated schema, lineage and ownership metadata.
- Define versioned, tested data-product and semantic-layer contracts with explicit ownership, quality expectations and deprecation paths.
- Apply AI-assisted, spec-driven and agentic workflows, and build internal tooling that helps teams scaffold configurations, models, contracts, tests and documentation.
- Collaborate with architects, product managers and staff developers on technical specifications, architecture reviews, proofs of concept and secure cloud-native design.
- Mentor other developers and foster continuous learning, quality and consistency with the north-star architecture.
Key requirements
- Degree in computer science, computer engineering or equivalent professional experience.
- 8+ years of scalable development experience with lead and software design accountabilities, including substantial data-platform and pipeline work.
- 2+ years in a technical leadership role on scalable platforms, technology transformation or modernization.
- Strong software design fundamentals, including domain-driven design, loosely coupled systems and event-driven services.
- Deep hands-on data engineering across streaming and batch, including Kafka, Flink or Debezium, schema evolution and delivery guarantees.
- Experience with lakehouse and medallion architecture on open table formats such as S3, Apache Iceberg, AWS Glue and Lake Formation, plus dbt.
- Experience with warehouse engines at scale and declarative orchestration such as Airflow.
- Track record making data discoverable, governed and trustworthy through metadata, catalog and lineage platforms such as DataHub and metadata-as-code.
- Experience with data contracts, schema governance, data quality, observability and service levels enforced automatically in CI and at runtime.
- Experience designing data products and a governed semantic layer, with Looker/LookML and familiarity with headless semantic layers such as dbt Semantic Layer or Cube as an asset.
- Extensive AWS cloud-native experience; working familiarity with GCP BigQuery and Looker; Azure a plus.
- Proficiency with agile delivery, infrastructure-as-code, DevSecOps, automated testing and CI/CD such as GitHub Actions or Jenkins.
- Seniority: Senior Staff
- Work mode: Hybrid (flexible)
- Key skills: AWS, Apache Iceberg, AWS Glue, Lake Formation, dbt, DataHub, Kafka, Flink, Debezium, Airflow, Looker, LookML, BigQuery, GCP, CI/CD
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