At a Glance
- Tasks: Build and maintain data integrations for cloud and SaaS platforms, ensuring data quality and visibility.
- Company: Join DoiT, a global tech leader in cloud solutions and innovation.
- Benefits: Enjoy unlimited vacation, flexible working, health insurance, and professional development opportunities.
- Other info: Work remotely with a diverse team that values inclusion and personal growth.
- Why this job: Make a real impact by enhancing customer insights and driving efficiency with cutting-edge technology.
- Qualifications: 3+ years in data engineering, strong SQL skills, and experience with cloud data warehouses.
The predicted salary is between 63000 - 77000 £ per year.
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.
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 out of them.
- Experience developing solutions in the cloud and/or using cloud services.
- Excellent communication skills in English, both written and verbal.
- Self-organized, goal-oriented and self-motivated; confident, thorough and tenacious.
Bonus Points:
- Experience with cloud or SaaS billing data - AWS/GCP/Azure cost and usage exports, marketplace billing, or the FOCUS specification.
- Familiarity with Go, which we use across our backend services.
- Experience with systems that carry financial or audit-grade correctness requirements - invoicing, metering, revenue reconciliation, or billing engines.
- Exposure to FinOps practices or cloud financial management products.
- BA/BS degree or equivalent practical experience.
Are you a Do'er? Be your truest self. Work on your terms. Make a difference. We are home to a global team of incredible talent who work remotely and have the flexibility to have a schedule that balances your work and home life. We embrace and support leveling up your skills professionally and personally. What does being a Do'er mean? We're all about being entrepreneurial, pursuing knowledge, and having fun!
Full-time employee benefits include:
- Unlimited Vacation
- Flexible Working Options
- Health Insurance
- Parental Leave
- Employee Stock Option Plan
- Home Office Allowance
- Professional Development Stipend
- Peer Recognition Program
DoiT unites as Many Do'ers, One Team, where diversity is more than a goal - it's our strength. We actively cultivate an inclusive, equitable workplace, recognizing that each unique perspective enhances our innovation. By celebrating differences, we create an environment where every individual feels valued, contributing to our collective success.
Data Engineer - Cloud & SaaS Integrations employer: Doit
DoiT is an exceptional employer that fosters a collaborative and innovative work culture, where creativity thrives and employees are empowered to make a real impact in the world of education. With a strong focus on professional growth, you will have access to continuous learning opportunities and the chance to influence the learning journeys of over 100,000 global learners in AI and design. Located in a vibrant environment, DoiT offers unique advantages such as flexible working arrangements and a commitment to diversity and inclusion, making it a truly rewarding place to work.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Cloud & SaaS Integrations
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We think you need these skills to ace Data Engineer - Cloud & SaaS Integrations
Some tips for your application 🫡
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How to prepare for a job interview at Doit
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