Data Engineer (Europe Hybrid / Remote)

Posted 5 months ago

SEON is the command center for fraud prevention and AML compliance, helping thousands of companies worldwide stop fraud, reduce risk and protect revenue. Powered by 900+ real-time, first-party data signals, SEON enriches customer profiles, flags suspicious behavior and streamlines compliance workflows – all from one place. SEON provides richer data, more flexible and transparent analysis, and faster time to value than any other provider on the market. We’ve helped companies reduce fraud by 95% and achieve 32x ROI, and we’re growing fast, thanks to our partnerships with some of the world’s most ambitious digital brands like Revolut, Wise, and Bilt.

We are currently looking for a skilled Data Engineer to join the Dataverse team. This role will report into the Data Engineering Lead and can be remote, ideally being based in the EU.

What You’ll Do:

Build, maintain, and optimize scalable ETL/ELT pipelines to process structured and unstructured data.
Experience in one or more of the following programming languages, python, Java, scala.
Automate workflows to ingest, transform, and store data in real-time or batch processing frameworks.
Architect and maintain cloud-based data platforms, such as Snowflake, BigQuery, or Redshift.
Manage and optimize relational and NoSQL databases for analytics and operational needs.
Partner with data scientists, analysts, and software engineers to deliver end-to-end data solutions.
Translate business requirements into data models, workflows, and engineering tasks.
Implement systems for data validation, lineage tracking, and quality monitoring.
Having Streaming knowledge is a plus (e.g. Apache Flink, spark streaming).
Ensure data security, compliance, and privacy standards are met (e.g., GDPR, HIPAA, SOC 2).
Monitor and enhance the performance of data systems to handle increasing scale and complexity.
Leverage big data tools (e.g., Apache Spark, Kafka) for processing and analytics.
Evaluate and implement emerging technologies to improve efficiency and performance.
Contribute to the establishment of best practices and reusable frameworks.

What You’ll Bring:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
3+ years of experience in data engineering, software development, or related roles.
Demonstrated success in building and maintaining scalable data pipelines and systems.
Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
Hands-on experience with big data tools like Spark, Hadoop, or Kafka.
Expertise with cloud platforms (AWS, Azure, GCP) and services such as S3, Lambda, and Dataflow.
Strong understanding of data modeling, warehousing, and architecture principles.
Ability to work with large datasets and solve complex data challenges.
Familiarity with BI tools like Tableau, Looker, or Power BI is a plus.
Strong problem-solving and critical-thinking abilities.
Excellent collaboration and communication skills for working across teams.
Fluent English knowledge

Amazing If You Also Have:

Experience with real-time data processing systems and event-driven architectures.
Familiarity with machine learning pipelines and model deployment.
Knowledge of DevOps and CI/CD practices for data engineering.