Senior Analytics Engineer

Senior Analytics Engineer

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
SoSafe

At a Glance

  • Tasks: Transform data with dbt, build models, and define key business metrics.
  • Company: Join SoSafe, a leading human risk management provider in Europe.
  • Benefits: Enjoy flexible hours, 33 vacation days, and corporate discounts.
  • Other info: Collaborative culture with opportunities for local meet-ups and virtual events.
  • Why this job: Make a real impact in cybersecurity while growing your career.
  • Qualifications: 5+ years in analytics engineering, strong SQL and dbt skills required.

The predicted salary is between 60000 - 80000 £ per year.

SoSafe has the ambition to become the leading human risk management provider in Europe. Our award-winning awareness platform triggers behavioural change by providing effective and engaging training and simulations on cybersecurity and data protection. Cybercrime is costing the world >$10 trillion annually and growing by 15% p.a. - we invite you to be part of the solution!

Location: UK, Ireland, or Portugal (remote). Candidates must have work authorization in one of these countries. Office access available in London, Dublin, and Lisbon.

Here’s how you’ll make a difference:

  • Own the transformation layer in dbt - design, build, and maintain modular, well-tested data models that define how data is structured and consumed across the company.
  • Define and implement core business metrics (e.g. activation, engagement, retention) as reusable, versioned data assets - ensuring consistent definitions across analytics, product, and AI use cases.
  • Model complex SaaS data by integrating product events, CRM (Salesforce), and support data into clean, well-defined fact and dimension models.
  • Build and evolve our semantic layer - creating a reliable abstraction over our data that enables consistent KPI definitions and supports downstream consumers, including LLM-based analytics agents.
  • Collaborate with Data Engineers on upstream data contracts and event schemas - ensuring raw data is structured in a way that supports scalable, reliable analytics.
  • Establish and enforce best practices in testing, documentation, and data quality - making these part of the standard development lifecycle.
  • Document models, metrics, and lineage clearly - enabling self-service and reducing ambiguity across teams.

What you bring:

  • 5+ years in analytics engineering or data engineering with a strong focus on data modeling.
  • Strong proficiency in dbt and SQL - building modular, well-tested models.
  • Solid understanding of dimensional modeling and metric design.
  • Experience working with cloud data warehouses (BigQuery, Snowflake, or Redshift).
  • Experience with metrics / semantic layers (e.g. dbt metrics, MetricFlow, Cube).
  • Strong data quality mindset (testing, validation, monitoring).
  • Comfortable working with event-based data and cross-functional teams.
  • Able to turn ambiguous business questions into clear data models.
  • Strong business acumen with the ability to challenge metric definitions and ensure they reflect real business outcomes.
  • Fluent in English.

Nice to have:

  • Familiarity with how LLMs consume structured data - e.g. semantic layers, metrics registries, YAML-based context - and an interest in building data infrastructure that serves AI agents, not just BI tools.
  • Experience modeling product usage data (event-based or session-based).

What we offer:

  • Work/Life balance: Flexible hours, 33 vacation days.
  • Wellbeing and financial support: Access to Open Up, corporate discounts.
  • Connection & community: Virtual events, collaborative team activities, and opportunities for local meet-ups.
  • And the list goes on: Tech equipment, referral bonuses, dog-friendly HQ.

Perks and benefits listed above are for full-time employees and may vary slightly by office location. These are just a sample - you will learn more during the interview process.

About Us: At SoSafe, we’re on a mission to make the digital world safer by addressing the human factor in cybersecurity. As one of the fastest-growing security awareness scale-ups worldwide, we leverage behavioural science and data-driven learning to empower people against cyber threats. Our Human Risk Management approach helps organisations turn their employees into their strongest line of defence. Backed by leading VCs like Highland Europe and Global Founders Capital, we’re rapidly expanding across the globe. We’re looking for team players who want to drive meaningful change in cybersecurity, take ownership of their work, and grow with us. If you thrive in a vibrant, purpose-driven environment that values innovation, diversity, and collaboration, then this is the place for you!

Senior Analytics Engineer employer: SoSafe

SoSafe is an exceptional employer that prioritises work-life balance with flexible hours and generous vacation policies, fostering a supportive and collaborative culture. Employees benefit from access to wellbeing resources, corporate discounts, and opportunities for professional growth in a rapidly expanding scale-up environment. With office locations in London, Dublin, and Lisbon, as well as remote work options, SoSafe offers a unique chance to contribute to meaningful change in cybersecurity while enjoying a vibrant community.

SoSafe

Contact Details:

SoSafe Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Analytics Engineer

Tip Number 1

Network like a pro! Reach out to current employees at SoSafe on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role. Personal connections can make a huge difference!

Tip Number 2

Prepare for the interview by brushing up on your technical skills. Since you’ll be working with dbt and SQL, practice building data models and solving real-world problems. Show us you can turn complex data into clear insights!

Tip Number 3

Don’t just focus on your technical skills; highlight your business acumen too! Be ready to discuss how your work has impacted business outcomes in the past. We want to see that you understand the bigger picture.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our mission to make the digital world safer.

We think you need these skills to ace Senior Analytics Engineer

dbt
SQL
Data Modelling
Dimensional Modelling
Metric Design
Cloud Data Warehouses (BigQuery, Snowflake, Redshift)
Metrics / Semantic Layers

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Analytics Engineer role. Highlight your proficiency in dbt, SQL, and data modelling, as these are key to what we’re looking for.

Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re passionate about cybersecurity and how your background makes you a great fit for our team. Don’t forget to mention any experience with cloud data warehouses or event-based data!

Showcase Your Projects:If you’ve worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing how you’ve applied your skills in real-world scenarios, especially around data quality and metric design.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our mission to make the digital world safer.

How to prepare for a job interview at SoSafe

Know Your Data Models

Make sure you brush up on your knowledge of data modelling, especially in dbt and SQL. Be ready to discuss how you've designed and maintained modular data models in the past, as this will be crucial for the role.

Understand Business Metrics

Familiarise yourself with core business metrics like activation, engagement, and retention. Be prepared to explain how you would define and implement these metrics as reusable data assets, ensuring consistency across different teams.

Showcase Your Collaboration Skills

Since this role involves working closely with Data Engineers and cross-functional teams, think of examples where you've successfully collaborated on projects. Highlight how you’ve ensured raw data is structured for scalable analytics.

Emphasise Data Quality Mindset

Demonstrate your strong data quality mindset by discussing your experience with testing, validation, and monitoring. Be ready to share specific instances where you established best practices in documentation and data quality.