Senior Data Engineer

Senior Data Engineer

Enode provides the infrastructure layer that makes it possible to connect and orchestrate devices at scale. We're hiring a Senior Data Engineer (with an interest in 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 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 lean 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—setting the direction for how the platform matures.
• 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 productionisation 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, bringing the experience to know when to build, when to buy, and when to leave well alone.

This role will be right for you, if:

• You're a senior 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 leading the data function in a small team: you bring structure, set priorities, and drive execution without needing heavy process. You've done this before, you know what good looks like, and you're energised by the autonomy to build it.
• 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 across multiple stages of a startup or scale-up.
• Pragmatic platform mindset: you can "improve the plane while flying" - make incremental improvements, manage trade-offs, and prioritise delivery over long platform rewrites.
• Ownership & proactivity: you identify what matters, push work forward, and operate effectively with high autonomy and limited oversight.
• Solid SQL + data modelling skills: comfortable designing datasets that are accurate, maintainable, and useful for analytics/modelling.
• Reliability instincts: you care about monitoring, data quality, testing, and operational excellence
• 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.).

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.