Hello. We’re Teya.

Teya was founded on a simple belief: local businesses deserve better.

They are the cafés, restaurants, salons, shops and entrepreneurs that bring character to our high streets, create jobs and keep communities moving. Yet for too long, financial services has made life harder for them - with clunky tools, poor support and complexity that gets in the way of running a business.

Teya exists to change that.

We’re building a financial platform for local businesses across Europe - one built around simple tools, thoughtful design and real human support. Our Members rely on us to help them run their business with confidence, and that responsibility shapes the way we work.

We move fast. We care about quality. We stay close to the detail. And we believe great performance and genuine hospitality should go hand in hand.

If you want to build meaningful products, solve real problems and make a genuine difference for local businesses, we’d love to hear from you

Your Role

We are seeking a Senior Data Engineer to join our team and help shape the future of our data platform. This role focus on data platform, building and maintaining the core data infrastructure, working on the entire lifecycle of data from our ingestion pipelines and their infrastructure to orchestration and governance.

You will play a key role in expanding the capabilities of our data platform, helping build new features that power decision-making across the organisation. This includes every stage of an ELT process, both at the pipeline level and the underlying infrastructure as well as working with engineering teams on how to best leverage our data..

As a senior member of the Data Engineering team, you will contribute to platform architecture, data product thinking, and engineering best practices, helping build a world-class scalable Data Platform that enables both analytics and future AI capabilities.

We want you to wonder about centralized vs decentralized provisioning of data tools, the trade-off between complex governance systems vs ease-of-use and data democratization, how to create simple processes to manage all the phases of the Data lifecycle and how to have some fun while doing it.

Your main responsibilities will include

Designing and evolving the architecture of our data infrastructure

Maintaining the existing data platform

Ensuring the reliability of our data ingestion pipelines

Propagating learnings in the Data Engineering team to other parts of Teya

Guaranteeing proper data governance following best practices, while not adding 100 steps of bureaucracy

Improving data reliability, quality, and observability across key datasets, while ensuring data pipelines are simple to set up.

Building, maintaining, and improving data models for large and complex datasets, while ensuring they have a simple lifecycle

Designing and optimising ETL/ELT pipelines to support scalable analytics and data products

Collaborate with data analysts, analytics engineering and engineering teams to turn their data platform use cases into reliable production solutions

Participate in the team's on-call rotation, investigate production incidents and contribute to improvements across Teya to prevent them from recurring.

Participate in technical discussions and code reviews, contributing to maintainable designs and strong engineering standards

Create and maintain clear technical documentation and operational runbooks

Your Story

5+ years experience in Data Engineering or Data Platform Engineering or Software Engineering working with Data

Strong SQL expertise, particularly in complex analytical and warehouse queries

Proficiency in Python and/or Java

Experience with Data Warehouses, such as Snowflake or Apache Iceberg

Practical knowledge deploying and operating containerised workloads using Docker and Kubernetes

Knowledge of streaming tooling (Kafka, Kafka Connect, Flink,…)

Experience with ETL/ELT tooling (dbt, Airflow, Airbyte, dlt,..)

Hands-on experience provisioning and managing cloud infrastructure with Terraform

Experience with CI/CD pipelines, automated testing and Git-based development workflows