Aimed at mid-to-senior level data engineers who thrive in collaborative, infrastructure-focused environments and have experience with modern data stack tools.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Talon.One
Talon.One, an Adyen company, is the most powerful incentives engine that unifies loyalty, personalized promotions and offer management into a single platform.
Built for enterprise scale and security, Talon.One helps businesses design and deliver incentives that drive real customer behavior.
Today, over 300 of the world’s most-loved brands including Sephora, Gymshark and Costa Coffee work with Talon.One to turn their incentives into a reliable growth engine.
ABOUT THE TEAM:
The Data team owns Talon.One's data infrastructure and the insights built on top of it: we design and operate the pipelines that bring data in and model it, and we turn that data into the analysis and reporting that guide decisions across the company. The team brings together data engineers, analytics engineers and data analysts, and continues to grow as Talon.One scales.
ABOUT THE ROLE:
You will be part of the Talon.One Data department, working closely with our Data Engineers and reporting into the Head of Data. Your responsibilities will span the full data lifecycle: owning and improving our data platform and ingestion pipelines, applying business logic and transformations to raw data (dbt, BigQuery), and partnering closely with stakeholders across the Infrastructure and Product Engineering teams.
ONCE YOU ARE HERE YOU WILL:
Own the data ingestion streams for all of our client’s DBs, from Postgres to BigQuery
Own the overall data infrastructure: set up, maintain and improve our stack with new technologies for more efficiency and best practices. E.g. improve orchestration
Write DWH pipelines and improve our overall DWH code to apply best practices and bring more efficiency.
Be part of a data team composed of various profiles, be at the center of all infrastructure decisions and work closely with other stakeholders from the R&D department, especially the DevOps team.
WHAT WE NEED YOU TO BRING TO THE TABLE:
2-4 years of experience in the Data Engineering / Data Ops field, ideally working on some big data warehouse projects
You are familiar with the modern data stack and are able to recommend, set up and maintain all different kinds of components from data ingestion to automation
You always thrive for applying data engineering best practices: consistency checks, testing data reliability, monitoring on top of ingestion pipelines, no double business logic in the code
Must have:
Data Orchestration: Airflow, Dagster, or similar
Containerization: Kubernetes
Relational Databases: PostgreSQL
Data Transformation: dbt
Nice to have:
Kafka
Strimzi
Google Cloud Platform
ABOUT TECHNOLOGY:
Kubernetes running on Google Cloud, ArgoCD, Terraform
PostgreSQL
Aiven Kafka Connect, Strimzi, Debezium
dbt cloud, GCP, BigQuery, Fivetran
We use Go for our API, core logic, and internal tooling
Cypress for automated end-to-end testing
Other odds & ends in JavaScript and shell script
WHAT'S IN IT FOR YOU:
A product & engineering team, now part of Adyen, building the incentives engine behind some of the world’s biggest brands
Adyen+, a significant monthly allowance to spend on whatever matters most to you and your wellbeing
28 days of paid annual leave
€115 monthly commuting allowance when you join us in the office 3 days per week
25% employer contribution to your pension
Annual all-company gathering at Adyen’s headquarters in Amsterdam, plus regional team events throughout the year
Opportunity to connect in person at Adyen offices across 29 locations worldwide
Source: Talon.One careers