Data Engineer
About Enode
The world’s energy use is changing - but the shift to renewables is too slow. Unlocking it requires smarter, more connected solutions.
Enode’s platform powers the next generation of green energy apps by connecting and optimizing the world’s energy devices through our APIs. From electric vehicles to heat pumps, we enable flexible demand that prioritises renewable energy.
We work with the world’s leading energy companies and green tech innovators, giving them instant access to over 250M+ consumers - and the ability to help millions of people use energy more sustainably.
With the urgent need to decarbonise, there has never been a more critical time for Enode. That’s why we’re backed by leading investors like Y Combinator, Lowercarbon Capital, and Creandum.
Yet, we’re just getting started - and we’re looking for builders and innovators to join our mission-driven, passionate team.
What we’re looking for:
We’re hiring a Data Engineer (with an interest working with data science) to own and evolve Enode’s data platform while partnering on our Flex product’s forecasting and analytics needs. You’ll help us scale from “it works” to “it works reliably as we grow”-ensuring the right data is available, trustworthy, and usable across Flex delivery, billing, customer insights, and leadership reporting.
You’ll be working directly with our Data Scientist, Håkon Kongelf, to drive Flex delivery and the next iteration of Enode’s data platform. You’ll collaborate closely with other engineers in our product teams, but also commercial teams and leadership to facilitate access to data and insights.
You’ll have outsized impact: this is a 2-person team, so your decisions and execution will shape how data work gets done across the company.
In this role, you will:
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 modelled 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.
This role will be right for you, if:
You’re a data engineer who likes shipping product outcomes, or a data scientist with strong engineering instincts who gets satisfaction from making pipelines stable, data trustworthy, and platforms scalable.
You enjoy working close to “real” problems: messy upstream inputs, ambiguous requirements, and high-stakes delivery. You can zoom in (fix a broken pipeline, optimize a model feature dataset) and zoom out (define what the platform should look like in 6–12 months).
You’re comfortable being a co-owner in a small team: you bring structure, propose priorities, and drive execution without needing heavy process. You care about impact, and you balance pragmatism with good engineering judgment.
You’re also excited about AI as a tool - whether that’s using it to speed up development, improve data quality workflows, or explore new ways of building and maintaining data products.
Must-haves:
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.
Nice to have:
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.).
What we offer:
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.
------------------------------------------------------------------------------------------
A few things to note:
Enode is an equal opportunities employer. Don’t meet every single requirement? Studies have shown that women and people of colour are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may just be the right candidate for this or other roles.
Our values are integral to the way we work and are embedded into all our hiring processes. You can read more about our values here.
About the job
Apply for this position
Data Engineer
About Enode
The world’s energy use is changing - but the shift to renewables is too slow. Unlocking it requires smarter, more connected solutions.
Enode’s platform powers the next generation of green energy apps by connecting and optimizing the world’s energy devices through our APIs. From electric vehicles to heat pumps, we enable flexible demand that prioritises renewable energy.
We work with the world’s leading energy companies and green tech innovators, giving them instant access to over 250M+ consumers - and the ability to help millions of people use energy more sustainably.
With the urgent need to decarbonise, there has never been a more critical time for Enode. That’s why we’re backed by leading investors like Y Combinator, Lowercarbon Capital, and Creandum.
Yet, we’re just getting started - and we’re looking for builders and innovators to join our mission-driven, passionate team.
What we’re looking for:
We’re hiring a Data Engineer (with an interest working with data science) to own and evolve Enode’s data platform while partnering on our Flex product’s forecasting and analytics needs. You’ll help us scale from “it works” to “it works reliably as we grow”-ensuring the right data is available, trustworthy, and usable across Flex delivery, billing, customer insights, and leadership reporting.
You’ll be working directly with our Data Scientist, Håkon Kongelf, to drive Flex delivery and the next iteration of Enode’s data platform. You’ll collaborate closely with other engineers in our product teams, but also commercial teams and leadership to facilitate access to data and insights.
You’ll have outsized impact: this is a 2-person team, so your decisions and execution will shape how data work gets done across the company.
In this role, you will:
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 modelled 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.
This role will be right for you, if:
You’re a data engineer who likes shipping product outcomes, or a data scientist with strong engineering instincts who gets satisfaction from making pipelines stable, data trustworthy, and platforms scalable.
You enjoy working close to “real” problems: messy upstream inputs, ambiguous requirements, and high-stakes delivery. You can zoom in (fix a broken pipeline, optimize a model feature dataset) and zoom out (define what the platform should look like in 6–12 months).
You’re comfortable being a co-owner in a small team: you bring structure, propose priorities, and drive execution without needing heavy process. You care about impact, and you balance pragmatism with good engineering judgment.
You’re also excited about AI as a tool - whether that’s using it to speed up development, improve data quality workflows, or explore new ways of building and maintaining data products.
Must-haves:
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.
Nice to have:
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.).
What we offer:
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.
------------------------------------------------------------------------------------------
A few things to note:
Enode is an equal opportunities employer. Don’t meet every single requirement? Studies have shown that women and people of colour are less likely to apply to jobs unless they meet every single qualification. We are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may just be the right candidate for this or other roles.
Our values are integral to the way we work and are embedded into all our hiring processes. You can read more about our values here.