IT Data Architect

17 ago - Italia
Shopfully

Who We Look For
We are looking for a Data Engineer to join our Engineering team in Europe. In this role, you will be a key player in building the next generation of our digital shopping marketplace. You'll work with massive datasets and cutting‐edge technologies like Spark, Kafka, and AWS to ingest, process, and distribute data at scale.
We need someone who doesn't just "move data" but treats data infrastructure as a product, enabling Data Scientists and Analysts to make informed, high‐impact decisions.
If you are passionate about data‐driven culture and eager to solve complex retail challenges, you're in the right place
What You Will Do
Join a team of talented data engineers who use cutting‐edge big data technologies to solve impactful business problems.
Work directly with Engineering, Data Science & Data Analysts teams to create both real‐time streaming and batch data pipelines that power data‐driven decisions across the organization.
Improve and maintain our data warehousing solutions and deliver trusted and easy‐to‐use datasets to both internal & external stakeholders.




Participate in design discussions with other team members and find innovative solutions to new and existing business problems.
Develop and enhance continuous integration and continuous delivery (CI/CD) pipelines for the team.
Explore new technology options for data processing, storage, and share them with the team.
Develop tools and contribute to internal & open source projects wherever possible.
What You Will Need
Bachelor's degree in Computer Science/Engineering or equivalent.
2+ years of work experience in building data pipelines ingesting and transforming large data sets.
2+ years of work experience in big data technologies such as Spark, Kafka, Airflow, etc.
Work experience in one or more general purpose programming languages, preferably Scala, Python.
Track record of shipping quality code and delivering high quality features.
You are passionate about data and driving a data‐driven culture in

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