Senior Analytics Engineer in London

Senior Analytics Engineer in London

London Full-Time 60000 - 80000 € / year (est.) No home office possible
Fin

At a Glance

  • Tasks: Design and manage scalable data pipelines while collaborating with cross-functional teams.
  • Company: Join Fin, a leading AI Customer Agent company transforming customer experiences.
  • Benefits: Enjoy a hybrid work environment, competitive salary, and opportunities for professional growth.
  • Other info: Embrace a diverse and inclusive culture focused on collaboration and creativity.
  • Why this job: Be part of an innovative team shaping the future of AI in customer service.
  • Qualifications: Advanced SQL skills and familiarity with modern data stacks are essential.

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

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration.

Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.

What is the opportunity? Intercom’s AI Group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta within weeks of a successful offline test. We constantly run experiments and measure the success of our AI features. We use frequentist and Bayesian approaches. We create dashboards to track results. We dive deep into exactly how users are being successful, and have to tease out all sorts of complex user interactions.

We are looking for a dedicated Analytics Engineer to join the AI Group to help us with that.

What will I be doing?

  • Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
  • Cross-functional Collaboration: Partner with AI analysts, ML scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
  • Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
  • Advanced Analytics & Insights: Conduct data analysis and build custom models to support strategic business decisions and performance measurement.
  • Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
  • Innovation in Data Infrastructure: Create scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
  • Strategic Influence: Work with partner teams to align data collection with long-term analytics and feature development goals.

About You

  • You write advanced SQL with a preference for well-architected data models, optimized query performance, and clearly documented code.
  • You’re familiar with the modern data stack. dbt and Snowflake experience are a big plus.
  • A growth mindset and eagerness to learn.
  • You exhibit great judgment and sharp business and product instincts that allow you to differentiate essential versus nice-to-have and to make good choices about trade-offs.
  • You practice excellent communication skills, and you tailor explanations of technical concepts to a variety of audiences.

Nice to haves

  • Exposure to Apache Airflow or other DAG frameworks — we use Airflow to orchestrate and schedule all of our data workflows and transformations.
  • Worked in Tableau, Looker, or similar visualization/business intelligence platform.
  • Experience with operational tools and business systems such as Google Analytics, Marketo, Salesforce, Segment, or Stripe.
  • Familiarity with Python.

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Senior Analytics Engineer in London employer: Fin

Fin is an exceptional employer, offering a dynamic work environment where innovation thrives and employees are empowered to push boundaries. With a strong commitment to employee growth, a hybrid working policy, and a radically open culture, Fin fosters collaboration and inclusivity while providing opportunities for professional development in the rapidly evolving field of AI and analytics. Join us in our mission to transform customer experiences and be part of a team that values your contributions and encourages continuous learning.

Fin

Contact Detail:

Fin Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Analytics Engineer in London

Tip Number 1

Network like a pro! Reach out to people in your industry, especially those at Fin or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.

Tip Number 2

Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to data pipelines or analytics. This gives potential employers a taste of what you can do beyond your CV.

Tip Number 3

Prepare for the interview by diving deep into Fin's products and values. Understand how your role as a Senior Analytics Engineer fits into their mission. Tailor your answers to show how you can contribute to their goals.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Fin team.

We think you need these skills to ace Senior Analytics Engineer in London

Advanced SQL
Data Pipeline Development
ETL Processes
Data Model Development
Data Quality Ownership
Data Warehouse Management
Data Analysis

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 advanced SQL skills and any experience with dbt or Snowflake, as these are key for us.

Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data and how you can contribute to our mission. Share specific examples of your past work that demonstrate your ability to innovate in data infrastructure.

Showcase Your Collaboration Skills:Since we value cross-functional collaboration, mention any experiences where you've worked with diverse teams. This will help us see how you can partner effectively with our AI analysts and engineers.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at Fin

Know Your Data Inside Out

As a Senior Analytics Engineer, you'll be expected to have a solid grasp of data models and SQL. Brush up on your advanced SQL skills and be ready to discuss how you've optimised query performance in past projects. Prepare examples that showcase your ability to design and manage scalable data pipelines.

Showcase Your Collaboration Skills

This role involves working closely with AI analysts, ML scientists, and engineers. Be prepared to share experiences where you successfully collaborated across teams. Highlight how you’ve tailored technical explanations for different audiences, as communication is key in this position.

Demonstrate Your Problem-Solving Mindset

Fin values innovation and efficiency. Think of specific instances where you streamlined data processes or improved reporting efficiency. Discuss any challenges you faced and how you overcame them, showcasing your growth mindset and eagerness to learn.

Familiarise Yourself with the Tools

If you have experience with dbt, Snowflake, or Apache Airflow, make sure to mention it! Even if you're not an expert, showing familiarity with these tools can set you apart. Do some research on how they fit into the modern data stack and be ready to discuss their applications.