Senior Data Engineer | GCP | Kafka | BigQuery | Python

Talentedge; Kraków; On-site; PLN 200,000 - 350,000; Full time

Job summary

Talentedge in Kraków is seeking a Senior Data Engineer to design, build and operate production-grade data pipelines on a modern GCP-based platform. You will work across batch and real-time environments, crafting robust data solutions with Python and SQL and building trusted data for analytics and AI/ML initiatives.

The role emphasizes data quality, observability, and adherence to engineering standards, with opportunities to mentor peers and influence platform design within a global fintech

Qualifications

• Proven track record building production data pipelines on GCP.
• Strong SQL and Python skills.
• Experience with Kafka or similar streaming systems.
• Familiar with BigQuery, Airflow, and GCS.
• Experience with dbt and data transformation.
• Understanding of Medallion architecture.
• Experience in regulated environments.

Responsibilities

• Design and build scalable batch and real-time data pipelines.
• Develop Kafka-based streams and Airflow workflows.
• Create and optimize data models in BigQuery.
• Maintain ingestion connectors and data integrations.
• Implement data quality, observability, and SLOs.
• Contribute to engineering standards and CI/CD practices.
• Support data science and AI-ready data initiatives.
• Mentor junior engineers and support team growth.

Skills

SQL

Python

GCP

Apache Kafka

BigQuery

Airflow/Cloud Composer

dbt

Medallion architecture

Data quality/observability

CI/CD

Tools

BigQuery

Airflow

Cloud Composer

GCS

Kafka

dbt

Cloud Run

Job description

A leading FTSE 100 fintech is looking for a Senior Data Engineer to join its global Data Engineering function and contribute to a major transformation of its data platform.

The team is consolidating a complex data estate onto GCP, creating a scalable and trusted platform that supports analytics, compliance, Data Science and increasingly sophisticated AI/ML use cases.

This is a hands‑on role suited to an experienced engineer who enjoys solving complex data problems and wants to have a meaningful influence on engineering standards and platform design.

The role

Working within a Data Engineering squad, you will design, build and operate production‑grade data pipelines across both batch and real‑time environments.

You will work across:

• GCP – BigQuery, Cloud Composer/Airflow, GCS and Cloud Run
• Apache Kafka – event‑driven ingestion and real‑time streaming
• Python and SQL – building reliable, production‑grade data solutions
• dbt – transformation and data modelling
• Medallion architecture – Bronze, Silver and Gold layers
• Data quality and observability – contracts, lineage, monitoring and SLOs

Role responsibilities

• Designing and building scalable batch and real‑time data pipelines
• Developing Kafka‑based event streams and Airflow‑orchestrated workflows
• Building transformations and data models in BigQuery
• Developing and maintaining ingestion integrations and connectors
• Implementing data quality controls, observability and pipeline monitoring
• Contributing to engineering standards, code reviews and CI/CD practices
• Supporting Data Science and AI‑ready data initiatives
• Mentoring junior engineers and contributing to the development of the wider engineering team

Role Requirements

• Strong commercial experience building and operating production data pipelines on GCP
• Strong SQL and Python skills
• Solid experience with Apache Kafka or comparable streaming technologies
• Experience with BigQuery, Airflow/Cloud Composer and GCS
• Experience with dbt and modern data transformation approaches
• Understanding of Medallion architecture and data platform best practices
• Experience with data contracts, lineage, observability and pipeline SLOs
• Experience working within a structured or regulated environment

This is an opportunity to work on large‑scale data engineering challenges within a global fintech, with the technical scope to make a real impact on the platform and how data is used across the organisation.