Data Engineering Team Lead

IG Index Limited

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Kraków - Poland Until 8/22/2026 First posted June 2, 2026 Last posted June 2, 2026
Job description

Job Title

Data Engineering Team Lead

Job Description

Minimum compensation: starting from 18 000 PLN. The final offer will be determined based on the candidate's experience and competencies.

So, who are we? 
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, onpremises 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. 

 
Your role in the Team’s Success 

As a Data Engineering Team Lead, you will own the delivery of critical data pipelines and platform capabilities that power analytics, compliance, and AI across IG. You will lead a squad of engineers across London, India, and Poland — setting technical direction, upholding engineering standards, and growing talent within the team. Reporting to the Head of Data Engineering, you will be the bridge between engineering execution and strategic platform goals, ensuring IG’s GCP-based data platform is reliable, scalable, and trusted by the business. 

 

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 

 

 

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) 

 

Key Qualification Requirements: 

 

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. Learn more about our D&I approach here. 

 

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.  

 
Learn more about the Perks here! 
 

Join us for this exciting journey.

Number of openings

1
About this role

Summary

Lead and develop data pipelines, oversee GCP platform, and mentor engineers.

Job title

Data Engineering Team Lead

Experience level

proven experience

Industry

fintech

Location requirements

Kraków, Poland; hybrid remote work allowed

Salary

$18k+

Management role

Yes

Skills & keywords

Required skills

GCPBigQueryAirflowKafkaSQL

Preferred skills

None specified

Specializations

data pipelinesGCPstreaming architecturesSQLdata quality
Locations

Structured locations inferred from the posting.

Kraków, Poland

Hybrid City