People Data Analyst: AI-Driven Insights

Enfuce; Finland; Remote; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Autonomy & ownership

Top-tier teammates

Growth opportunities

Flexible remote work

Supportive culture

Employee stock option program

Flexible paid time off

Team activity budget

Healthcare / pension where available

Job summary

Enfuce is building the most sustainable issuer processing platform in Europe and is looking for a Data Analyst to clean and structure people data for reliable insights. You will collaborate with the People and Data & AI teams to enable reporting and AI-powered products, starting with foundation work and expanding into analytics at scale.

You bring 3+ years of data analytics experience, strong SQL, and hands-on dbt, with a track record in modern BI tools and secure data handling.

Qualifications

• 3+ years of experience as a Data Analyst, taking messy raw data through to a clear insight and a recommendation. Experience embedded in a business function is even better.
• Strong SQL skills and experience with modern cloud data platforms, such as Snowflake (preferred), BigQuery, or Databricks. You're comfortable working with large datasets and understanding how data moves from source systems into analytical models.
• Hands‑on experience with dbt or similar analytics engineering practices. You know how to build maintainable transformation pipelines, structure models, test and document data, and manage dependencies between datasets.
• Comfort with Git‑based development workflows. Version control, branches, pull or merge requests, code review, and collaborative development are a normal part of how you work.
• Strong experience with modern BI and analytics platforms, such as ThoughtSpot (preferred), Looker, or Omni. You've built dashboards and analytical experiences that people genuinely use, and you understand how the BI layer connects to the underlying data models and sources.
• Experience working with sensitive data and analytics access controls. You understand concepts such as role‑based access, row‑level security, column‑level security, data masking, and least‑privilege access, and can apply them pragmatically when working with sensitive People data.

Responsibilities

• Build a data foundation we can trust. Get our people data clean and reliable, own the quality across our systems, and move our reporting to ThoughtSpot together with the central Data & AI team. Very few People teams have ever done this properly.
• Turn data into direction. Dig into where we lose time, what causes friction, and what really drives engagement and retention. Bring us ideas that come out of what you've found, and give our leaders something they can act on.
• Connect people's data to the business. Linked up with Finance it makes headcount planning and forecasting much sharper. Built into our leading and lagging indicators, it shows how our people connect to what the business is trying to achieve.
• Prove what we build works. Set the success measures before we build something, then go back afterwards and check whether it was delivered. We'd rather find out quickly and change course than be right slowly.
• Power the AI builds. Work with the People Product Lead on agents, automations and AI-powered people products. You'll build the data layer they run on and measure what they're worth. This part of the role grows as we go.

Skills

Data analysis

SQL

Analytics engineering with dbt

Git workflows

BI platforms

Data security controls

Tools

Snowflake

BigQuery

Databricks

dbt

ThoughtSpot

Looker

Omni

Job description

Enfuce is building the most sustainable issuer processing platform in Europe and is looking for a Data Analyst to clean and structure people data for reliable insights. You will collaborate with the People and Data & AI teams to enable reporting and AI-powered products, starting with foundation work and expanding into analytics at scale.

You bring 3+ years of data analytics experience, strong SQL, and hands-on dbt, with a track record in modern BI tools and secure data handling.