Senior Data Engineer

Description

IG Group is a FTSE 100 fintech operating across five continents, serving over 1.4m 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 perks:

• Competitive salary & benefits plan

• Life Insurance

• MyBenefit Platform

• Medical Insurance with Medicover

• 1 additional day off to celebrate your Birthday

• 2 additional days off a year for voluntary work

• Share Plans for Employees

• Free lunch at the office (ones per week)

• Employee Assistance Program

• We work in hybrid working model

What You'll Need:

• Proven hands-on experience building and operating production-grade data pipelines on GCP — including BigQuery, Cloud Composer/Airflow, GCS, and Cloud Run — with strong SQL and Python skills

• Solid experience with Apache Kafka or equivalent streaming technologies, including designing event-driven ingestion patterns and troubleshooting real-time data flows under operational conditions

• Familiarity with modern transformation tooling, particularly dbt, and an appreciation of Medallion (Bronze/Silver/Gold) architecture patterns and how they support self-service analytics

• A quality-first mindset: experience implementing data contracts, lineage tracking, observability tooling, and pipeline SLO monitoring in a production environment

• Comfortable working in a regulated financial services environment, with an understanding of data governance requirements (lineage, access control, audit trails) and the discipline to operate within change control processes

What you’ll do:

• Design and build robust batch and real-time data pipelines on GCP, including Kafka-based event streams, BigQuery transformations, and Airflow-orchestrated workflows, as part of the GCP consolidation and Medallion architecture build-out

• Own data quality within your delivery area: define and implement data contracts, quality checks, and observability instrumentation so that pipeline health is visible and SLAs are met

• Develop and maintain in-house connectors and third-party native integrations that form part of IG’s ingestion estate, ensuring resilience, monitoring, and long-term maintainability

• Contribute to engineering standards and best practices across the squad — including code review, dbt modelling patterns, CI/CD pipeline hygiene, and change control for shared datasets

• Support feature engineering and model data pipelines for Data Science, and help lay the foundations for AI-ready data — including lineage, reproducibility, and freshness guarantees for ML workloads