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

Apply Now

Senior AI Data Engineer

Tripledot
City of London
1 day ago
Create job alert

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

Senior AI Data Engineer

Department: Engineering

Employment Type: Permanent - Full Time

Location: London, UK

Description

Tripledot is one of the largest independent mobile games companies in the world.

We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios.

Our expanded portfolio includes some of the biggest titles in mobile gaming, collectively reaching top chart positions around the world and engaging over 25 million daily active users.

Tripledot's guiding principle is that when people love what they do, what they do will be loved by others.

We're building a company we're proud of - one filled with driven, incredibly smart and detail-orientated people, who LOVE making games.

Our ambition is to be the most successful games company in the world, and we're just getting started.

Role Overview

Working within a group function that is aimed to work with all group studios. Within the group AI functions you'll be working with other AI/ ML Eng, Data engineers, analysts and product owners..

Within the various studios you will interact with data, engineering, and product teams. The group AI function's goal is to make Tripledot an AI first company. You'll be reporting into the VP of AI. The role will be directly contributing to main games KPIs such as retention, revenue, player experience, as well as to company efficiency and time to market in developing games and features.

Progression opportunities will be within the AI group or to studios in the group. The first initiative you'll be taking part of is LTV predictions both for Ad based revenues and IAP based ones.

Key Responsibilities
  • Design, build, and maintain scalable and reliable data pipelines to support AI/ML initiatives across the studio.
  • Collaborate with data scientists, ML engineers, analysts, and game developers to understand data needs and translate them into robust infrastructure solutions.
  • Develop and maintain ETL/ELT workflows that ingest and transform structured and unstructured data from various sources (e.g., game telemetry, player behavior, marketing).
  • Work with cloud platforms (e.g., AWS, GCP) to manage and optimize data lakes, warehouses (e.g., BigQuery, Snowflake), and orchestration tools (e.g., Airflow).
  • Ensure data quality, consistency, and governance across all stages of the data lifecycle.
  • Monitor and troubleshoot data pipelines and ensure timely delivery of data to downstream systems.
  • Enable real-time and batch data processing to support AI use cases like player segmentation, churn prediction, personalization, and content optimization.
  • Advocate for best practices in data engineering, including CI/CD, version control, testing, and observability.
Required Skills, Knowledge and Expertise
  • 4+ years of experience as a Data Engineer, ideally within gaming, mobile apps, or digital products.
  • Strong proficiency in SQL and Python.
  • Experience with OLAP Databases.
  • Understanding of DBT.
  • Hands-on experience with data pipeline orchestration (e.g., Airflow, Prefect, Dagster).
  • Experience with big data technologies and distributed systems (e.g., Spark, Kafka, Flink).
  • Familiarity with machine learning workflows, feature stores, and model serving is a plus.
  • Solid understanding of cloud infrastructure (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
  • Passion for gaming and an interest in using AI to create better player experiences.
  • Strong Data Modelling skills.
  • A collaborative mindset with strong communication skills and a product-focused approach.
Working at Tripledot
  • 25 days paid holiday in addition to bank holidays to relax and refresh throughout the year.
  • Hybrid Working: We work in the office 3 days a week, Tuesdays and Wednesdays, and a third day of your choice.
  • 20 days fully remote working: Work from anywhere in the world, 20 days of the year.
  • Daily Free Lunch: In the office you get GBP 12 every day to order from JustEat
  • Regular company events and rewards: quarterly on-site and off-site events that celebrate cultural events, our achievements and our team spirit.
  • Employee Assistance Program: Anytime you need it, tap into confidential, caring support with our Employee Assistance Program, always here to lend an ear and a helping hand.
  • Family Forming Support: Receive vital support on your family forming/ fertility journey with our support program [subject to policy]
  • Life Assurance & Group Income Cover: Financial protection for you and your loved ones.
  • Continuous Professional Development
  • Private Medical Cover & Health Cash Plan
  • Dental Cover
  • Cycle to Work Scheme
  • Pension Plan


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior AI Data Engineer

Sr. AI Data Engineer (UK Remote)

Sr. AI Data Engineer (UK Remote)

Sr. AI Data Engineer (UK Remote)

Sr. AI Data Engineer (UK Remote)

Sr. AI Data Engineer (UK Remote)

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.

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.