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Data Engineering Team Lead

Kraków - Poland

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Employment
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Apply at IG Group

What you’ll work on

Full posting
  • 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

From the employer’s posting
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
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
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

What you’ll bring

All qualifications

Core experience

  • 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
  • 1 additional day off to celebrate your Birthday
  • 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
  • 2 additional days off a year for voluntary work
  • 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
Qualification wording
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
1 additional day off to celebrate your Birthday
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
2 additional days off a year for voluntary work
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

Tools in this posting

  • SQL
  • AWS
  • BigQuery
  • Google Cloud (GCP)
  • Google Cloud Storage
  • Kafka
  • dbt
  • Airflow
Source — Tool mentions in context
- 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)
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:
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
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

Job description

View original posting ↗

Job Title

Data Engineering Team Lead

Job Description

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:


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

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:



  • 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) 

 

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 

Number of openings

1

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  • Check the listed location, eligibility and core experience before starting.
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Location & working pattern

Kraków - Poland

- Employee Assistance Program - We work in hybrid working model Number of openings
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First seen by us
Jun 3, 2026
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Last seen by us
Oct 9, 2026

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