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Head of Data

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

Leadership experience, Strong development skills in Python, Experience with data platforms (Snowflake, DBT, etc.), Proven data pipeline and systems integration experience, Fluency in English.

Key responsabilities:

  • Lead check-ins and standups to align team goals
  • Develop Scrive’s BI solutions for insights
  • Spearhead analyses for data-driven decision-making
  • Collaborate with teams to integrate data sources
  • Oversee data pipeline selection and storage management

Job description

You will be a part of…
...an international environment with colleagues all around Europe with our headquarters in Stockholm, Sweden. You will join a fast and innovative environment and be a part of a great-positioned company, with even higher ambitions for the future. Scrive is filled with caring, smart and committed people who know that we need to collaborate to win. We care about each other and encourage ourselves and each other in our aim to be better and grow, both as people and as a company. Come join us and be a part of Scrive’s successful journey! 🚀

Are you passionate about transforming data into actionable insights? As Head of Data at Scrive, you’ll play a key role in shaping our data-driven future, enabling teams across the company to make smarter decisions.

Reporting directly to the Director of R&D, you’ll lead a small but powerful data team within the Engineering department, collaborating closely with commercial teams (Sales, Customer Success, Support) and Operations. While we prefer someone based in the Stockholm area, this role offers flexibility to work remotely from anywhere within the EU.

Your challenge
As our Head of Data, you will be driving force in making Scrive more data-driven across all departments, from Sales and Customer Success to Operations. With a clear focus on developing and maintaining our BI solutions, your role is critical in helping our teams make decisions based on solid data, not gut feelings.

In your daily work, you will:

  • Lead regular check-ins and daily standups to ensure your team is aligned and focused on goals

  • Maintain and develop Scrive’s BI solution to provide key insights into customer usage and performance

  • Propose and spearhead new analyses that empower data-driven decision-making company-wide

  • Collaborate closely with the Engineering and Commercial teams to integrate data from multiple sources and generate powerful reports and insights

  • Oversee the entire data pipeline, from selecting tools to reconfiguring storage, modelling data sets, and suggesting new reporting features

  • Ensure company-wide transparency by making critical business information accessible across departments.

What you’ll bring
We’re looking for someone who thrives in a technical and strategic role. To succeed in this position, you’ll need:

  • Leadership experience

  • Strong development skills in Python

  • Experience with data platforms like Snowflake, DBT, Count or Prefect

  • Proven experience in reconfiguring data pipelines and developing integration code for new systems

  • A passion for using data to drive business outcomes.

  • Fluency in English, both written and spoken

🌟 Also, big bonus points if you:

  • Are living in the Stockholm area

  • Have experience working with enterprise data systems

  • Have worked in a high-growth/scale-up environment

  • Have a passion for business intelligence and using data to create a competitive advantage

In this role we see that you are building relationships and networking, taking initiatives and results oriented. We’re using a competence-based recruitment process where those competences will play an important role.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
EnglishEnglish
Check out the description to know which languages are mandatory.

Other Skills

  • Problem Solving
  • Collaboration
  • Leadership
  • Analytical Thinking
  • Verbal Communication Skills

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