At a Glance
- Tasks: Lead the design and operation of large-scale data pipelines on GCP.
- Company: Join IG Group, a leading fintech with a global presence.
- Benefits: Tailored development programs, mentoring, and extra time off for volunteering.
- Other info: Hybrid working model with a focus on collaboration and diversity.
- Why this job: Tackle complex problems and shape the future of data engineering.
- Qualifications: Experience in GCP, data pipelines, and team leadership required.
The predicted salary is between 90000 - 110000 £ per year.
IG Group is a FTSE 100 fintech operating across five continents, serving over 1.3m customers and handling billions of dollars in transactions – built on scale, trust, and proof. We didn’t pivot to innovation; it’s how we’ve always operated. What that means for the people who work here is real: genuinely complex problems to solve, the technology and resources to tackle them properly, and the kind of scope that’s rare in established businesses. The bar is high – bring a curious and forward-thinking mindset and we’ll give you the platform to define what comes next. Join us at IG – the future gets built here.
Your team IG’s Data function is a central capability serving both central and divisional business lines across the entire IG estate. The Data Engineering team is responsible for the platforms that underpin analytics, reporting, compliance, and client-facing data products, and that will increasingly power AI and machine-learning use cases across the firm. The current data landscape reflects IG’s growth: a combination of GCP-native capabilities, on-premises systems, and a legacy AWS data platform. The strategic direction — endorsed by the CDO and Executive — is clear: consolidate onto GCP, raise the bar on data quality, and enable self-service access to trusted data for teams across the business.
What you’ll do:
- Own the technical architecture of IG’s GCP data platform end-to-end — Core Lake (BigQuery), batch and real-time (Kafka) ingestion, transformation in the Medallion architecture, and Data-Engineering-owned integration services — setting the reference designs and patterns squads build against.
- Lead delivery of the most complex, high-risk work within the GCP consolidation programme, including migration off the legacy AWS platform and on-premises systems onto GCP-native capabilities.
- Define the platform contracts, interfaces, and self-service patterns that let mature divisions build and own their own models safely against trusted Core Lake data, and ensure fully-managed builds for less-mature functions follow the identical pattern so they are handover-ready by design.
- Drive data quality as a first-class, firm-wide concern: establish data contracts, observability, SLA/SLO monitoring, and automated alerting and remediation across ingestion and transformation layers, and hold squads to those standards.
- Act as the senior technical point of contact for stakeholders across Compliance, Marketing, Finance, Data Science, and the self-serving divisions (UK, APAC, tastytrade/US, Quants, Risk), translating requirements into well-scoped, well-architected engineering deliverables.
- Set and uphold engineering standards through code and design reviews, technical mentoring, and reusable frameworks that raise the bar across squads in London, India, and Poland — growing the technical capability of the whole function.
- Provide technical direction and quality assurance for third-party staff augmentation, ensuring augmented capacity engaged for time-boxed projects works to IG’s patterns and leaves behind maintainable, standards-compliant assets.
- Maintain delivery rigour: shape sprint cadences, escalate technical risk early, and report on pipeline SLOs, data freshness, and DORA-style engineering metrics to the Head of Data Engineering and CDO.
What you’ll need for this role:
- Hands-on experience designing and operating large-scale data pipelines on GCP (BigQuery, Cloud Composer/Airflow, GCS), with proven knowledge of Apache Kafka and real-time streaming architectures.
- Demonstrated experience leading or technically mentoring a team of data engineers, with the ability to set standards, conduct code and design reviews, and grow engineers’ capabilities.
- Strong grasp of data quality practices: data contracts, pipeline observability, SLA/SLO definition, and automated alerting and remediation.
- Solid understanding of SQL transformation patterns and modern tooling such as dbt, alongside experience managing ingestion estates with third-party connectors and in-house integrations.
- Clear and confident communicator able to work cross-functionally with non-technical stakeholders; comfortable in a regulated financial services environment with structured delivery disciplines (sprint cadences, change control, escalation).
How we work:
We try to take a thoughtful approach to our ways of working as a company. We follow a hybrid working model with 3 days in the office – which we think balances the need to collaborate effectively and connect with each other. When it comes to how we deliver, there are 5 things we want everyone to do to drive high performance, better learning and career satisfaction:
- Lead and Inspire: Drives trust, alignment, and enthusiasm.
- Think Big: Focus on the problems that most impact commercial outcomes.
- Champion the client: Understand and prioritise client’s needs.
- Deliver at pace: Push for fast, sustainable growth.
- Raise the bar: Take ownership, be accountable and share feedback.
We believe that diversity is vital to success, it fuels creativity, drives innovation and sets us up for global success. We’re committed to building teams with a variety of perspectives and skills to help us realise our vision and strategy, that’s why we encourage applications from people with diverse backgrounds and experiences to join us on this journey.
The Perks:
Your growth fuels our success! Thrive with tailored development programs, mentoring opportunities with leaders, and clear career progression. Expand your network through committees, sports and social clubs. Enjoy extra time off for volunteering and community work.
Join us for this exciting journey.
Principal Data Engineer employer: IG Group
IG Group is an exceptional employer located in the heart of London, offering a vibrant work culture that fosters innovation and collaboration. Employees benefit from a commitment to professional growth through continuous learning opportunities and the chance to work with cutting-edge AI tools in a dynamic fintech environment. With a focus on flexibility and efficiency, IG Group ensures that its team members thrive while contributing to meaningful recruitment processes.
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We think this is how you could land Principal Data Engineer
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We think you need these skills to ace Principal Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at IG Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at IG Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.