About IG Group
IG Group is a FTSE 100 fintech operating across five continents, serving over 1.3m customers and handling billions of dollars in transactions. The company focuses on complex problem solving and innovation.
The Data Engineering Team
IG’s Data function is a central capability serving both central and divisional business lines. The 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. The current landscape includes GCP-native capabilities, on-premises systems, and a legacy AWS data platform. The strategic direction is to consolidate onto GCP, raise the bar on data quality, and enable self-service access to trusted data.
Responsibilities
- 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.
- 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.
- 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.
- Drive data quality as a first-class, firm-wide concern: establish data contracts, observability, SLA/SLO monitoring, and automated alerting and remediation.
- Act as the senior technical point of contact for stakeholders across Compliance, Marketing, Finance, Data Science, and the self-serving divisions.
- Set and uphold engineering standards through code and design reviews, technical mentoring, and reusable frameworks.
- Provide technical direction and quality assurance for third-party staff augmentation.
- Maintain delivery rigour: shape sprint cadences, escalate technical risk early, and report on pipeline SLOs, data freshness, and DORA-style engineering metrics.
We follow a hybrid working model with 3 days in the office. 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.
Requirements
- 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).
