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

Apply Now

Senior Data Engineer

Sharp Gaming
Manchester
2 days ago
Create job alert

About Us

Our mission is to dominate the betting and gaming industry on a global scale and we need the very best Tech talent to help us achieve this.

We recently migrated all of our customers onto our very own proprietary platform - so it's an exciting time to join us. With the help of our new platform, we're able to pioneer new products and drive more advanced, creative technologies. The result? Unrivalled experiences for millions of customers worldwide.

Betfred's Technology department is driven by innovation, and you'll be at the heart of unlocking our new platform's potential. So, if you want to help shape the future of betting and gaming, then it's time to join us.

Job Purpose

This Senior Data Engineer will play a key role in the evolution of our data platform, driving innovation and delivering high-quality data solutions. This role will focus on developing cutting edge real-time data solutions including automation, business intelligence, and enabling analytics.

Job Duties

  • Design, develop, and maintain data pipelines and ETL processes using AWS services such as AWS Glue, AWS Lambda and AWS S3.
  • Support the migration of the existing Data Warehouse from SQL Server to AWS through S3 and Redshift.
  • Develop and implement data quality checks and validation procedures.
  • Design and implement best practice data lakehouse architectures and data warehousing solutions.
  • Collaborate with data scientists and analysts to support the deployment of machine learning and advanced analytical solutions.
  • Develop and maintain data documentation and operational procedures.
  • Investigate and resolve data quality issues and performance bottlenecks.
  • Stay abreast of the latest data technologies and industry best practices.
  • Mentor junior data engineers and provide technical guidance to other team members where applicable.
  • Contribute to the development and improvement of data platform best practices.

Knowledge, Skills and Experience

  • Good understanding of AWS services such as AWS Glue, AWS Lambda, AWS S3, AWS Redshift, and Amazon EMR.
  • Proficiency in Python, SQL, Pipeline Orchestration, and data warehousing concepts.
  • Ability to diagnose and resolve complex data issues.
  • Ability to effectively communicate with both technical and non-technical stakeholders.
  • Experience with data lakehouse architectures and data warehousing solutions
  • Experience with Agile development methodologies
  • Experience with data security and privacy best practices

What’s in it for you?

We offer a variety of competitive benefits, some of which vary depending on the role you’re recruited to. Some of what you can expect in this role includes:

  • A competitive rate of pay and pension contribution (£60,000-£80,000)
  • Generous discretionary bonus schemes, incentives and competitions
  • An annual leave entitlement that increases with length of service
  • Access to an online GP 24/7, 365 days a year for you and your immediate family.
  • Employee wellbeing support through our Employee Assistance Programme
  • Enhanced Maternity & Paternity Pay
  • Long Service Recognition
  • Access to a pay day savings scheme, financial coach and up to 40% of your earned wage ahead of payday, through Wagestream.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

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.