Data Engineer
Kraków - Poland
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and build batch and real-time data pipelines on GCP, including Kafka streams and BigQuery transformations
Own data quality: define data contracts, quality checks and pipeline observability
Develop and maintain in-house connectors and third-party ingestion integrations
Contribute to engineering standards, code review, dbt patterns and CI/CD hygiene
Support feature engineering and model data pipelines for Data Science
From the employer’s posting
Design and build robust batch and real-time data pipelines on GCP, including Kafka-based event streams, BigQuery transformations, and Airflow-orchestrated workflows
Own data quality within your delivery area: define and implement data contracts, quality checks, and observability instrumentation
Develop and maintain in-house connectors and third-party native integrations that form part of IG’s ingestion estate
Contribute to engineering standards and best practices across the squad — including code review, dbt modelling patterns, CI/CD pipeline hygiene
Support feature engineering and model data pipelines for Data Science
What you’ll bring
All qualificationsCore experience
- Solid experience with Apache Kafka or equivalent streaming technologies, including designing event-driven ingestion patterns and troubleshooting real-time data flows under operational conditions
- 1 additional day off to celebrate your Birthday
- Familiarity with modern transformation tooling, particularly dbt, and an appreciation of Medallion (Bronze/Silver/Gold) architecture patterns and how they support self-service analytics
- 2 additional days off a year for voluntary work
Qualification wording
Solid experience with Apache Kafka or equivalent streaming technologies, including designing event-driven ingestion patterns and troubleshooting real-time data flows under operational conditions
1 additional day off to celebrate your Birthday
Familiarity with modern transformation tooling, particularly dbt, and an appreciation of Medallion (Bronze/Silver/Gold) architecture patterns and how they support self-service analytics
2 additional days off a year for voluntary work
Tools in this posting
- Python
- SQL
- AWS
- BigQuery
- dbt
- GCP
- Google Cloud Storage
- Kafka
- Airflow
Source — Tool mentions in context
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
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 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
- 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
- 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
Posting record
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- Live
- First seen by us
- Aug 17, 2026 · 67 days ago
- Recorded sightings
- 102
- Last seen by us
- Oct 23, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
Job Title
Data EngineerJob Description
Compensation details will be shared by the recruiter during the first interview.
So, who are we?
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 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 Engineer, build, and operate the data pipelines and platform capabilities that power IG’s analytics, compliance, and AI ambitions. Working within a squad led by the Data Engineering Team Lead, you will be a key technical contributor to IG’s GCP consolidation programme — tackling complex ingestion, transformation, and reliability challenges with a high standard of craft. You will also play a meaningful role in raising the bar for the wider team: mentoring junior engineers, championing data quality, and helping to define how the squad builds and operates at scale.
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
The Perks
It really is more than a job. We think like a start-up, but we deliver like a FTSE 100 — so the bar is high, and we won't pretend otherwise.
We work hybrid, which means three days in the office. We’ll recognise your talent and make sure that you can still have a life – at work, and outside of it. Networks, committees, awards, sports and social clubs, mentorships, volunteering opportunities, extra time off… the list goes on.
- 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
1Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Kraków - Poland
It really is more than a job. We think like a start-up, but we deliver like a FTSE 100 — so the bar is high, and we won't pretend otherwise. We work hybrid, which means three days in the office. We’ll recognise your talent and make sure that you can still have a life – at work, and outside of it. Networks, committees, awards, sports and social clubs, mentorships, volunteering opportunities, extra time off… the list goes on. - Competitive salary & benefits plan
More source context
- Employee Assistance Program - We work in hybrid working model Number of openings
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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