Data Engineer

Location: Remote (UK, Ireland, Estonia, Netherlands, Sweden, Israel) or Contract (Eastern Europe, Portugal).

Who We Are: DoiT is a global technology company specializing in cloud-driven solutions for business growth and innovation. We combine data, technology, and human expertise to help customers operate efficiently across multicloud environments. With decades of experience in Kubernetes, GenAI, CloudOps, and partnerships with AWS, Google Cloud, and Microsoft Azure, we serve over 4,000 customers worldwide.

The Opportunity

Cloud spend is evolving beyond traditional cloud providers. Our customers increasingly rely on SaaS platforms, data clouds, and AI vendors, each with unique billing APIs and pricing models. DoiT’s Integrations Framework consolidates this fragmented data into a unified, trustworthy cost picture.

We’re hiring a Data Engineer to expand visibility by integrating more vendor spend data into our platform. Your role involves:

• Expanding vendor coverage: Build integrations with third-party billing APIs, ensuring accurate and comprehensive spend data. Adapt to constant API and pricing changes to scale coverage efficiently.
• AI-augmented workflow: Leverage AI tools daily for tasks like code exploration, prototyping, debugging, testing, and documentation. Push boundaries on AI’s capabilities while maintaining quality standards.
• Data correctness and completeness: Ensure high-quality data by addressing duplication, gaps, race conditions, and deduplication. Implement checks and reconciliations to validate financial decisions.
• Normalization across vendors: Design models to standardize diverse vendor bills into comparable formats (units, currencies, time granularity, taxonomies, and cost categories).
• Pipeline ownership: Manage orchestration, scheduling, and backfill mechanics for ingestion pipelines. Make backfills routine, safe, and self-service.
• Collaboration and problem-solving: Work closely with product, support, and engineering teams to identify gaps and propose solutions. Proactively drive improvements without waiting for specifications.

Qualifications

• 3+ years of professional experience in data engineering or a data-heavy backend role, with production ownership of pipelines.
• Proficient in SQL, capable of writing, reading, and optimizing complex analytical queries.
• Hands-on experience with data pipelines and orchestration frameworks. Dagster or Airflow is highly preferred; experience with Prefect, dbt, or similar tools is relevant.
• Strong Python skills or another language for data work.
• Experience with cloud data warehouses or analytical stores like BigQuery, ClickHouse, Snowflake, or Redshift.
• Experience integrating third-party REST APIs, including handling pagination, rate limits, partial failures, and unreliable documentation.
• Instinct for data correctness—reconcile totals, question plausible numbers, and build assertions rather than assuming accuracy.
• AI-augmented working style: Actively use AI tools in your workflow and can articulate their impact.
• Experience with cloud development or cloud services.
• Excellent communication skills in English (written and verbal).
• Self-organized, goal-oriented, and tenacious.

Bonus Points

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

Are you a Do’er? Join a global team that values flexibility, professional growth, and a fun, entrepreneurial culture. Benefits include unlimited vacation, flexible work options, health insurance, parental leave, stock options, home office allowances, and professional development stipends.

DoiT embraces diversity and inclusivity, fostering an environment where every perspective drives innovation.