Quick overview
Job description
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
- 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
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