D
Data Engineer - Cloud & SaaS Integrations
DoiT
Contract type
Ongoing
Work mode
100% remote
Experience
3 years
Job description
Key details
- Build new integrations against third-party billing and usage APIs to expand vendor coverage and make more customer spend visible in the platform
- Keep existing integrations current as vendors change their APIs and pricing models, and drive down the marginal cost of the next integration
- Work AI-augmented daily across the full span of work, including exploring unfamiliar codebases and third-party APIs, prototyping, generating and reviewing code, debugging, writing tests, and producing documentation
- Own data correctness and completeness, including duplication, gaps, race conditions in ingestion and reprocessing, deduplication of spend arriving via cloud marketplaces, and support for negotiated rates
- Build checks and reconciliation to prove the numbers are right
- Design and build models that normalize dozens of differently-shaped vendor bills across units, currencies, time granularity, resource and service taxonomies, and cost categories
- Own orchestration, scheduling, and backfill mechanics for ingestion
- Company mission
- DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation, combining data, technology, and human expertise to help customers operate in a well-architected and scalable state
Primary stack
Core technologies
SQL
Benefits
- Information not specified
Requirements & details
- Full-time employee based remotely in the UK, Ireland, Estonia, the Netherlands, Sweden, or Israel; contractors in Eastern Europe and Portugal also considered
- Experience building integrations against third-party billing and usage APIs
- Strong data engineering skills for data correctness, completeness, and normalization across vendors
- Experience owning orchestration, scheduling, and backfill mechanics for ingestion pipelines
- Ability to work AI-augmented across the full workflow with judgement about where AI raises velocity and where human quality control is required
- Information not specified
- SQL
