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

• Map out what people data we have (and where it lives)


• Clean it up, structure it, and make it usable


• Coordinate across functions to maintain data quality maintenance


• Help define consistent metrics (headcount, attrition, hiring, etc.)


• Work with People Ops, Finance, and systems owners to fix gaps

2. Build reporting we can trust

• Move us away from one-off reports and manual pulls


• Create repeatable, reliable reporting


• Own core dashboards (headcount, attrition, hiring, diversity, etc.)


• Make sure numbers actually reconcile across teams


• Upskill the team on basic reporting and use of tools

3. Create dashboards people will actually use

• Build simple, clear dashboards for:


• People team


• Leadership


• Focus on insight, not just data dumps


• Use modern tools (BI platforms, not just spreadsheets)

4. Support compensation & benefits analytics

• Partner closely with C&B on:


• Gather all the benefit data from various sources and systems


• benefits usage and cost analysis


• pay analysis

5. Help us get more AI/data-savvy

• Bring ideas on how we can use AI/tools to:


• automate reporting


• surface insights faster


• reduce manual work


• We’re not looking for hype - just practical improvements that work

6. Improve how our systems talk to each other

• Work across HRIS, ATS, payroll, and other tools


• Help improve data flows and integrations (with support from tech where needed)


• Be the person who actually understands how people data connects end-to-end

What you'll have:

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


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


• Built dashboards and reporting in a real business setting


• Strong google sheets and excel user


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


• 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


• Explaining data in a way non-data people understand


• 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:

• a hands-on builder role


• a chance to shape people data from the ground up


• high ownership, high visibility

This isn’t:

• a pure reporting role


• a perfectly set-up data environment


• a big team (you’ll be the go-to person for this)

What success looks like (first 12 months)

• We have trusted, consistent people metrics


• Core dashboards are in place and actually used


• Manual reporting is significantly reduced, and colleagues can self serve


• People & reward decisions are backed by data


• Leaders can answer basic people questions without asking 3 different teams

This listing is from ats_lever. View original listing ↗