Staff Data Engineer

Booksy Inc.
London
20 hours ago
Applications closed

Related Jobs

View all jobs

Staff Data Engineer

Staff Data Engineer

Staff Data Engineer

Staff Data Engineer

Staff Data Engineer

Staff Data Engineer

A career at Booksy means you’re part of a global team focused on helping people around the world feel great about themselves, every day. From empowering entrepreneurs to build successful businesses, to supporting their customers in arranging 'me time' moments, we’re in the business of helping people thrive and feel fantastic.

Working in an ever-changing, scale-up environment where things are messy and resources are limited isn't for everyone. If you thrive in a stable environment with big budgets, clear processes, and structures, then we’re probably not the right fit. However, if you love bringing order to chaos, inventively solving problems, and carving your own path within ambiguity, then you’re likely to love it here.

As a Marketing Data Engineering Lead (Staff Engineer) reporting to the Head of Data Engineering in our Data Engineering team, your purpose will be to design and own the technical foundation that proves and improves marketing ROI at Booksy. You’ll transform complex data from ad platforms, CRM, and automation tools into a trusted marketing data mart — the single source of truth for measuring performance, enabling attribution, and powering personalized campaigns that fuel our growth.

  • Proven expertise in building and maintaining data pipelines ingesting complex marketing and advertising platform APIs (Google Ads, Meta Ads, TikTok, AppsFlyer, Iterable, etc.).
  • Strong SQL skills and mastery of Dataform, with experience designing clean, performant, and modular data models supporting attribution and funnel analysis.
  • Deep experience with Google Cloud Platform (GCP), particularly BigQuery, including cost- and performance-optimized schema design.
  • Advanced knowledge of Customer Data Platforms (Segment.io), including event stream management, identity resolution, and building a “Golden Profile.”
  • Hands-on experience designing and implementing Reverse ETL pipelines (e.g., with Census or Hightouch) to activate customer data in marketing systems like Iterable or CRMs.
  • Strong collaboration skills, able to partner with architects and stakeholders to translate business needs into scalable data systems.
  • Experience mentoring engineers and setting high standards for data quality, testing, and documentation.

At a minimum, we require conversational English language skills. Why? English is our company language and is used for all business-wide communications, so you need to be able to speak English to be an integrated part of Booksy.

  • The opportunity to be part of something big — the world’s fastest-growing beauty marketplace.
  • Flexible working hours and the opportunity to work remotely within your country.
  • Work in a welcoming team always ready to help.
  • Opportunity to develop in an international environment — we have teams in 6 countries.
  • Additional benefits that may vary depending on location.

Our Diversity and Inclusion Commitment:

We operate in a highly creative and diverse industry, and we strive to create an inclusive environment for all. We welcome people from all backgrounds and are committed to fair consideration in our hiring process. If you have accessibility needs or require reasonable adjustments during the interview process, please contact us at , so we can support you.

Please submit your application and CV in English to ensure it is reviewed successfully.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.