Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Backend Data Engineer

SimilarWeb LTD
London
3 days ago
Create job alert
Overview

Our unique data and solutions empower over 4,300 customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies. In 2021, we went public on the New York Stock Exchange, and we continue to reach new heights! Come work alongside Similarwebbers across the globe who are bright, curious, practical and good people.

Job Summary

We are looking for a skilled Data / Backend Engineer to join our high-performing Data Labs team and help design high-scale systems that retrieve, process, and analyze digital data. You'll build and maintain robust backend infrastructure and data pipelines that power Similarweb's most strategic, data-driven solutions. This customer-facing role is ideal for someone who enjoys a fast-paced environment and thrives on solving complex technical challenges. You'll work with leading global brands, helping them unlock insights from our unique datasets.

Responsibilities
  • Design and build high-scale systems and services to support data infrastructure and production systems.
  • Develop and maintain data processing pipelines using technologies such as Airflow, PySpark and Databricks.
  • Implement dockerized high-performance microservices and manage their deployment.
  • Monitor and debug backend systems and data pipelines to identify and resolve bottlenecks and failures.
  • Work collaboratively with data scientists, analysts, and other engineers to develop and maintain data-driven solutions.
  • Serve as an engineering focal point, promoting best practices and enforcing architectural and coding standards.
Qualifications
  • BSc degree in Computer Science or equivalent practical experience.
  • At least 4+ years of server-side software development experience in languages such as Python, Java, Scala, or Go.
  • Experience with Big Data technologies like Spark, Databricks, and Airflow.
  • Familiarity with cloud environments such as AWS or GCP and containerization technologies like Docker and Kubernetes.
  • Strong problem-solving skills and ability to learn new technologies quickly.
  • Excellent communication skills and ability to work in a team-oriented environment.
Nice to Have
  • Familiarity with microservices architecture and API development.
  • Knowledge of databases like Redis, PostgreSQL, and DWH (such as Redshift, Snowflake, etc.).


#J-18808-Ljbffr

Related Jobs

View all jobs

Backend Data Engineer in London - Similarweb

AI Engineer - Data/MLOps

Senior Data Engineer, Events Bucharest, Romania

Data Engineer (AI/Analytics Pipeline)

Senior Data Engineer - Data/Backend

Data Engineer in Manchester - Tax.com

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.

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.