Data Engineer

Description

Compensation details will be shared by the recruiter during the first interview.

The Perks

• Home office equipment reimbursement

• Performance relate bonus

• Private medical cover for you and your family/partner (Medicover)

• Multikafeteria system (you can choose a multisport card, vouchers, etc.)

• Life insurance (Generali)

• LinkedIn Learning platform free access

• Share Plans for Employees

• Well-being events as well as Employee Assistance Programme

• Summer picnic, New Year party and other social events

• Three additional days off a year - one to celebrate your Birthday and two for voluntary work

• App-based parking spots booking system

• Stretching sessions

How we work

• 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;

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

What you’ll need for this role

• 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

• Raise the bar: Take ownership, be accountable and share feedback