Software Engineer II (Python) - Supply & Demand
On-siteAthens, Attica, Greece
Job Summary
Own a commodity balance end-to-end by taking half-defined blending rules through computation, validation, and a reliable production release on the Airflow pipeline, including on-call support. Lead resolution of critical bugs in pipelines, databases, and distribution APIs, converting each incident into a runbook and prevention. Extend the anomaly-detection gate using Prophet-based tools to catch bad numbers before publication, while generalizing the data model and ETL framework for scalable commodity additions. Build and evolve TypeScript services for oil and grains distribution APIs, design well-scoped milestones, and write ADRs. Onboard and mentor junior engineers through pairing and code reviews. Partner with Research, Product, and Data to transform ambiguous needs into deliverable tasks, and actively participate in hiring loops as a calibrated interviewer.
Required Qualifications
- 2+ years of experience as a software engineer, with experience delivering production systems.
- Experience owning a non-trivial feature or service end-to-end in production (design, ship, monitor, and fix), not just delivered tickets.
- Strong Python for data-heavy work (e.g. pandas/polars, SQLAlchemy or equivalent ORM, a relational database with real schema evolution).
- Comfortable debugging and operating production data pipelines, and has carried on-call or first-responder duty for systems they built.
- Has taken a half-defined problem and shaped it into a delivered solution without waiting to be told the route.
Desired Qualifications
- Experience with workflow orchestration (Airflow / Astronomer or similar) and batch/ETL data pipelines.
- TypeScript/Node API experience (NestJS, Express, tsoa, TypeORM) for the distribution-API surface.
- Exposure to commodities, energy, or any domain with messy, multi-provider data that must be reconciled.
- Has mentored a junior engineer or onboarded a new joiner.
- Familiarity with anomaly detection / forecasting (Prophet, scikit-learn) or data-quality tooling.
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