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, its own pricing model, and its own idea of what a "line item" means. DoiT's Integrations Framework is what 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, so this is genuine, permanent ownership with a short line 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. This is the core of the role. Build new integrations against third-party billing and usage APIs, and get more of our customers' spend visible in the platform. Keep existing integrations current as vendors change their APIs and pricing models - which they do constantly. Drive down the marginal cost of the next integration 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. Push on what the tooling can do for this codebase, and bring judgement about where AI raises velocity and where a human still has to hold the quality bar.
• Data correctness and completeness. Own the quality of the data our integrations produce: duplication, gaps, and race conditions in ingestion and reprocessing, deduplication of spend that also arrives via cloud marketplaces, and support for customers' negotiated rates rather than public list pricing. Build the checks and reconciliation that let us prove the numbers are right rather than hope they are.
• Normalization across vendors. Design and build the models that make dozens of differently-shaped vendor bills comparable - consistent units, currencies, time granularity, resource and service taxonomies, and cost categories.
• Pipeline ownership. Own the orchestration, scheduling, and backfill mechanics for ingestion pipelines end-to-end - including making backfills a routine, safe, self-service operation.
• Collaborating and problem-solving. Work with product, support, and the engineers building on top of this data to understand where the gaps hurt. Propose work you think should happen; you're not here to wait for a spec.

Qualifications

• 3+ years of professional experience in data engineering or a data-heavy backend role, with production ownership of pipelines that other people depend on
• Strong SQL - you can write, read and reason about the performance of non-trivial analytical queries
• Hands-on experience building and operating data pipelines with an orchestration framework. Dagster or Airflow is highly desired ; equivalent experience with Prefect, dbt or a comparable tool is relevant if you're ready to work in Dagster/Airflow
• Strong Python , or another language you use fluently for data work
• Experience with a cloud data warehouse or analytical store ( BigQuery , ClickHouse, Snowflake, Redshift or similar)
• Experience integrating third-party REST APIs, including handling the realities: pagination, rate limits, partial failures, late-arriving and restated data, and vendors whose documentation is wrong
• A real instinct for data correctness. You are the kind of engineer who reconciles totals, questions a number that looks plausible, and builds the assertion rather than assuming
• AI-augmented working style - you already use AI tools across your engineering workflow and can talk concretely about what you've got …