Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Data Engineer

John Goddard Associates
City of London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Join to apply for the Senior Data Engineer role at John Goddard Associates

2 days ago Be among the first 25 applicants

Join to apply for the Senior Data Engineer role at John Goddard Associates

Get AI-powered advice on this job and more exclusive features.

Up to £95,000 + benefits | Hybrid (3 days a week in City of London)

A global financial services firm is hiring a Senior Data Engineer to join their Brokerage technology team.

You'll be building and maintaining the data pipelines that underpin their £1bn+ broking business - with a strong focus on improving brokerage data quality, optimising commercial analysis, and supporting complex client agreements.

This is a hands-on engineering role working closely with stakeholders and system owners. You'll be expected to code daily (Python), manage Airflow pipelines (MWAA), build ETL processes from scratch, and improve existing workflows for better performance and scalability.

Key Responsibilities

  • Design and build robust ETL pipelines using Python and AWS services
  • Own and maintain Airflow workflows
  • Ensure high data quality through rigorous testing and validation
  • Analyse and understand complex data sets before pipeline design
  • Collaborate with stakeholders to translate business requirements into data solutions
  • Monitor and improve pipeline performance and reliability
  • Maintain documentation of systems, workflows, and configs

Tech environment

  • Python, SQL/PLSQL (MS SQL + Oracle), PySpark
  • Apache Airflow (MWAA), AWS Glue, Athena
  • AWS services (CDK, S3, data lake architectures)
  • Git, JIRA

You Should Apply If You Have

  • Strong Python and SQL skills
  • Proven experience designing data pipelines in cloud environments
  • Hands-on experience with Airflow (ideally MWAA)
  • Background working with large, complex datasets
  • Experience in finance or similar high-volume, regulated industries (preferred but not essential)
  • High attention to detail and a clear commitment to data quality

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

LNKD1_UKTJSeniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionInformation Technology
  • IndustriesData Infrastructure and Analytics

Referrals increase your chances of interviewing at John Goddard Associates by 2x

Get notified about new Senior Data Engineer jobs in City Of London, England, United Kingdom.

London, England, United Kingdom 1 day ago

Senior Data Analyst, Reporting & Operations

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 month ago

Slough, England, United Kingdom 4 days ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 19 hours ago

Senior Data Analysts and Full Stack DevelopersData Architect - 18 month FTC London/Hybrid - Up to £74kSenior Consulting Analyst - Private Equity Data & TechnologySenior Data Analyst, Reporting & Operations

London, England, United Kingdom 2 weeks ago

EMEA Senior Data Centre Systems Design Engineer

Slough, England, United Kingdom 2 weeks ago

London, England, United Kingdom 21 hours ago

London, England, United Kingdom 2 weeks ago

Data Architect – Clinical Knowledge Graph

London, England, United Kingdom 3 weeks ago

Contract Data Architect (Modelling) - FS - London (Hybrid) - £600pd Outside IR35

London, England, United Kingdom 4 weeks ago

Principal Solution Engineer – AI and Data Use Governance

London, England, United Kingdom 2 weeks ago

Senior Lead Software Engineer - Team Lead - Accelerator Business

London, England, United Kingdom 6 days ago

London, England, United Kingdom 2 months ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#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.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has quickly become one of the most transformative forces in modern technology. What began as a subset of artificial intelligence—focused on algorithms that learn from data—has grown into a foundational capability across industries. From voice assistants and recommendation systems to fraud detection and predictive healthcare, machine learning underpins countless innovations shaping daily life. In the UK, demand for ML professionals has surged. Financial services, healthcare providers, retailers, and tech start-ups are investing heavily in ML talent. Roles like Machine Learning Engineer, Data Scientist, and AI Researcher are among the most sought-after and best-paid in the tech sector. Yet we are still only at the start. Advances in generative AI, quantum computing, edge intelligence, and ethical governance are reshaping the field. Many of the most critical machine learning jobs of the next 10–20 years don’t exist yet. This article explores why new careers will emerge, the kinds of roles likely to appear, how today’s jobs will evolve, why the UK is well positioned, and how professionals can prepare.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.