Data Engineer
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Job Description
Data Engineer owning and evolving Enode’s data platform while collaborating on Flex product analytics needs. Enhancing data quality and enabling self-serve analytics for a climate tech startup.
Responsibilities:
- Deliver Flex-critical data needs: build and maintain reliable pipelines and datasets that enable Flex models (e.g., demand/availability signals, aggregations, monitoring).
- Evolve the data platform: assess what we have today and drive pragmatic improvements in architecture, tooling, and operating practices.
- Own data quality and trust: implement testing, lineage/definitions, and guardrails (e.g., dbt tests, anomaly detection, freshness checks) so stakeholders can trust outputs.
- Enable self-serve analytics: produce well modeled datasets and documentation that make it easy for others to answer questions without bespoke work.
- Partner on data science work: collaborate on data readiness for modelling, feature pipelines, evaluation workflows, and productionization concerns (even if you’re not the primary model builder).
- Make high-leverage tech choices: propose and justify changes (or non-changes) to tools and processes, prioritizing impact and delivery over long platform rewrites.
Requirements:
- Strong data engineering background: you’ve built or evolved data pipelines/platforms in production (ideally in a startup/scale-up).
- Pragmatic platform mindset: you can “improve the plane while flying”—make incremental improvements, manage trade-offs, and prioritize delivery.
- Ownership + proactivity: you identify what matters, push work forward, and can operate effectively in a small team with high autonomy.
- Solid SQL + data modeling skills: comfortable designing datasets that are accurate, maintainable, and useful for analytics/modeling.
- Reliability instincts: you care about monitoring, data quality, testing, and operational excellence (not just building new pipelines).
- Clear communication: you can collaborate with engineers, product, and business stakeholders, and translate needs into concrete data work.
- Familiarity with parts of the modern data stack; dbt, data warehousing ELT tools (Snowflake, Airbyte) and BI tools
- Experience supporting forecasting & time-series use cases (or high-volume event data).
- Interest in (or exposure to) energy markets / flexibility / trading.
- Experience designing data access, governance, and cost-aware warehouse usage in a growing org.
- Strong interest in AI, with evidence of experimenting (LLM-assisted workflows, automation, evaluation, etc.).
Benefits:
- Opportunity to join and impact an early-stage climate tech startup with global aspirations as we scale.
- A mission-driven, fun and caring environment with high drive and ambition.
- Competitive compensation, including a very attractive employee option program - you’re part of our journey.
- Remote-first in Europe, with the option of attending an office in Oslo or receiving a co-working pass on demand.
- Three annual off-sites to connect with the team in exciting & fun places.
- Flexible, human-first culture.
- Stipend for setting up your home office.
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