Data Engineer - Cloud & SaaS Integrations

About DoiT

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 integration ecosystem. 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: Build new integrations against third-party billing and usage APIs, and bring more customer spend into the platform. Keep existing integrations current as vendors change APIs and pricing models. Drive down the marginal cost of future integrations so coverage scales faster.
• Working AI-augmented: Use AI daily across your full engineering workflow — exploring unfamiliar codebases and third-party APIs, prototyping approaches, generating and reviewing code, debugging, writing tests, and producing documentation.
• Data correctness and completeness: Own data quality across ingestion and reprocessing pipelines, handle spend deduplication from cloud marketplaces, and support negotiated rates. Build automated checks and reconciliation systems to prove metrics accuracy.
• Normalization across vendors: Design and build models that make dozens of differently-shaped vendor bills comparable — consistent units, currencies, time granularity, resource/service taxonomies, and cost categories.
• Pipeline ownership: Own end-to-end orchestration, scheduling, and backfill mechanics for ingestion pipelines, ensuring backfills are routine, safe, and self-service.
• Collaborating and problem-solving: Partner with product, support, and engineering teams to identify data gaps and propose technical solutions proactively.

Qualifications

• 3+ years of professional experience in data engineering or a data-heavy backend role, with production ownership of critical data pipelines.
• Strong SQL skills: ability to write, read, and optimize non-trivial analytical queries.
• Hands-on experience building and operating data pipelines with an orchestration framework (Dagster or Airflow highly desired; Prefect or dbt acceptable if ready to transition).
• Strong Python proficiency (or another language fluently used for data engineering).
• Experience with cloud data warehouses or analytical stores (BigQuery, ClickHouse, Snowflake, Redshift, or similar).
• Experience integrating third-party REST APIs, handling pagination, rate limits, partial failures, late-arriving data, and inaccurate vendor documentation.
• Strong instinct for data correctness, auditability, and building automated assertions.
• Proven AI-augmented working style using AI tools across engineering workflows.
• Experience developing cloud-native solutions.
• Excellent written and verbal communication skills in English.

Bonus Points

• Experience with cloud or SaaS billing data (AWS/GCP/Azure cost exports, marketplace billing, or the FOCUS specification).
• Familiarity with Go.
• 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