People Data & Analytics Specialist

Help us use technology to make a big green dent in the universe!

Kraken powers some of the most innovative global developments in energy.

We’re a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone.

It’s a really exciting time in energy. Help us make a real impact on shaping a better, more sustainable future.

Why this role exists

Right now, our people data setup is… let’s say early stage.

We operate across ~20 countries, but

• data sits in different places
• reporting is mostly manual
• definitions aren’t always consistent
• dashboards are limited
• and we’re not getting the insights we should be
• At the same time, the business is growing fast and expects proper, data-backed decisions — especially around hiring, retention, compensation, and benefits.
• This role exists to help us go from reactive spreadsheets → actual people insights.

What you'll do

1. Get control of the data

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• Map out what people data we have (and where it lives)
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• Clean it up, structure it, and make it usable
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• Coordinate across functions to maintain data quality maintenance
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• Help define consistent metrics (headcount, attrition, hiring, etc.)
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• Work with People Ops, Finance, and systems owners to fix gaps

1. Build reporting we can trust

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• Move us away from one-off reports and manual pulls
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• Create repeatable, reliable reporting
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• Own core dashboards (headcount, attrition, hiring, diversity, etc.)
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• Make sure numbers actually reconcile across teams
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• Upskill the team on basic reporting and use of tools

1. Create dashboards people will actually use

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Build simple, clear dashboards for

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• People team
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Leadership

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• Focus on insight, not just data dumps
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• Use modern tools (BI platforms, not just spreadsheets)

1. Support compensation & benefits analytics

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Partner closely with C&B on

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• Gather all the benefit data from various sources and systems
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• benefits usage and cost analysis
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• pay analysis

1. Help us get more AI/data-savvy

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Bring ideas on how we can use AI/tools to

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• automate reporting
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• surface insights faster
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• reduce manual work
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• We’re not looking for hype - just practical improvements that work

1. Improve how our systems talk to each other

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• Work across HRIS, ATS, payroll, and other tools
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• Help improve data flows and integrations (with support from tech where needed)
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• Be the person who actually understands how people data connects end-to-end

What you'll have

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1–5 years experience working with data, analytics, or BI

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Preferably come from a tech, SaaS, or product-led environment

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Built dashboards and reporting in a real business setting

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Strong google sheets and excel user

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Essential to be comfortable with SQL and know the basics of python or dbt modelling

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Are comfortable working in messy or evolving data environments

👉 You don’t need to come from HR or People Analytics - we’re happy with candidates from broader data/analytics backgrounds who are interested in applying those skills to people data.

You’re good at

• Turning unclear questions into structured analysis

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• Explaining data in a way non-data people understand
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• Spotting inconsistencies and fixing them

• Balancing detail with speed (not over-engineering everything)

Bonus if you

• Have exposure to people/HR data, compensation, or workforce analytics
• Have worked with multiple systems and data sources

What this role is (and isn’t)

This is

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• a hands-on builder role
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• a chance to shape people data from the ground up
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• high ownership, high visibility

This isn’t

• a pure reporting role

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• a perfectly set-up data environment
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• a big team (you’ll be the go-to person for this)
• What success looks like (first 12 months)
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• We have trusted, consistent people metrics
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• Core dashboards are in place and actually used
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• Manual reporting is significantly reduced, and colleagues can self serve
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• People & reward decisions are backed by data
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• Leaders can answer basic people questions without asking 3 different teams