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Beamery is a jobs, skills, and tasks data platform that helps organizations navigate AI and automation by enabling informed decisions across talent lifecycle management. The platform powers recruitment, mobility, upskilling, diversity, work architecture, and workforce planning for leading global companies.
As Senior Data Engineer, you will own significant end-to-end components of Beamery's data platform, which powers reporting and underpins the company's AI strategy. You'll design, build, and operate production data pipelines and the analytics layer that enables the entire organization to make faster, data-driven decisions.
Key responsibilities include:
- Building and running production data pipelines: design, implement, and operate scalable ETL pipelines and storage systems, owning uptime and data correctness.
- Developing the analytics and semantic layer: model core business metrics and feature usage signals into clean, trustworthy data products for BI, self-service analytics, and AI consumers.
- Enabling data self-service: build monitoring, alerting, and data-quality checks that allow other teams to trust and use the platform independently.
- Raising the bar for the team: mentor engineers and improve patterns for coding, data modeling, and pipeline design through code review and pairing.
You'll work within an evolving architecture alongside Engineering, Product, and Design teams. The role requires someone who has built and operated production data platforms (warehousing, lakes, streaming, and batch), owned pipelines through failure and fixed them properly, and can work autonomously while communicating clearly with technical and business stakeholders.
Required experience: dbt, SQL/NoSQL schema design and data modeling, Python backend engineering, streaming and batch pipelines, data quality and observability practices, infrastructure as code (Terraform, Kubernetes). The current stack includes dbt, BigQuery, Kafka, PostgreSQL, MongoDB, Typescript/Node.js, Kubernetes, and Segment, though the ability to learn new tools matters more than specific tool expertise.
