Data Engineering Team Lead

Description

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.

The perks:

• Competitive salary & benefits plan

• Life Insurance

• My Benefit 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:

• 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)

What you’ll do

• Lead and deliver data pipeline and platform work within the GCP consolidation programme, owning squad commitments end-to-end across batch and real-time (Kafka) workloads

• Coach, develop, and performance-manage a squad of data engineers, fostering a culture of engineering excellence, ownership, and continuous improvement

• Drive data quality as a first-class concern: embed data contracts, observability, and SLA monitoring across ingestion and transformation layers in the Medallion architecture

• Act as the technical point of contact for stakeholders in Compliance, Marketing, and Data Science, translating requirements into well-scoped engineering deliverables

• Maintain delivery rigour: run sprint cadences, manage commitments, escalate risks early, and report on pipeline SLOs, data freshness, and DORA-style engineering metrics