Data Engineer - Cloud & SaaS Integrations

Location

Our Data Engineer will be an integral part of our R&D team. This role is based remotely as a full-time employee in the UK, Ireland, Estonia, the Netherlands, Sweden, and Israel. We are also open to contractors in Eastern Europe and Portugal.

Who We Are

DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state — from planning to production.

Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency.

With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work alongside more than 4,000 customers worldwide.

The Opportunity

Cloud spend is no longer just AWS, Google Cloud, and Azure. Our customers now run a large and growing share of their technology spend through SaaS platforms, data clouds, and AI vendors — each with its own billing API, pricing model, and definition of a "line item." DoiT's Integrations Framework turns that into a single, trustworthy picture of cost.

We're hiring a Data Engineer to own the data side of this. Your mandate is expanding visibility — bringing more of a customer's spend into the platform, from more vendors, at a quality bar people can make financial decisions on. The vendor landscape moves constantly, offering genuine, permanent ownership with a direct link from your work to what customers see.

You'll work AI-augmented from day one. We expect you to use AI across your whole workflow, not as an occasional autocomplete, and to have real opinions about where it earns its place.

Responsibilities

• Expanding vendor coverage: Build new integrations against third-party billing and usage APIs to bring more customer spend into the platform. Keep existing integrations current as vendors modify APIs and pricing models. Drive down the marginal cost of subsequent integrations so coverage scales faster.
• Working AI-augmented: Use AI daily across the full span of your work — exploring unfamiliar codebases and third-party APIs, prototyping approaches, generating and reviewing code, debugging, writing tests, and producing documentation. Bring judgment about where AI raises velocity versus where a human must maintain quality.
• Data correctness and completeness: Own the quality of data integrations produce: duplication, gaps, race conditions in ingestion and reprocessing, deduplication of marketplace spend, and support for negotiated rates over list pricing. Build assertion checks and reconciliation mechanics.
• Normalization across vendors: Design and build models that make differently-shaped vendor bills comparable — aligning units, currencies, time granularity, resource taxonomies, and cost categories.
• Pipeline ownership: Own orchestration, scheduling, and backfill mechanics for ingestion pipelines end-to-end, making backfills a routine, safe, self-service operation.
• Collaborating and problem-solving: Partner with product, support, and engineering teams to identify gaps and propose technical solutions proactively.

Qualifications

• 3+ years of professional experience in data engineering or a data-heavy backend role with production pipeline ownership.
• Strong SQL skills to write, read, and reason about the performance of complex analytical queries.
• Hands-on experience building and operating data pipelines with an orchestration framework (Dagster or Airflow preferred; Prefect or dbt experience is relevant if ready to transition).
• Strong Python or equivalent language fluency for data engineering.
• Experience with a cloud data warehouse or analytical store (BigQuery, ClickHouse, Snowflake, Redshift, or similar).
• Experience integrating third-party REST APIs (handling pagination, rate limits, partial failures, late-arriving/restated data, and undocumented API behavior).
• Strong instinct for data correctness, auditing, assertion building, and numerical reconciliation.
• AI-augmented working style with concrete experience using AI tools across your engineering workflow.
• Experience developing solutions in the cloud using native cloud services.
• Excellent communication skills in English (written and verbal).
• Self-organized, goal-oriented, confident, and proactive.

Bonus Points

• Experience with cloud or SaaS billing data (AWS/GCP/Azure cost & usage exports, marketplace billing, or the FOCUS specification).
• Familiarity with Go (used across backend services).
• Experience with systems requiring financial or audit-grade correctness (invoicing, metering, revenue reconciliation, billing engines).
• Exposure to FinOps practices or cloud financial management products.
• BA/BS degree or equivalent practical experience.

Benefits

• Unlimited Vacation
• Flexible Working Options
• Health Insurance
• Parental Leave
• Employee Stock Option Plan
• Home Office Allowance
• Professional Development Stipend
• Peer Recognition Program