Senior Data Engineer @

3 days ago


Budapest, Budapest, Czech Republic SEON Technologies Full time

What you bring:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
  • 5+ 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.
  • Strong problem-solving and critical-thinking abilities.
  • Excellent collaboration and communication skills for working across teams.
  • Fluent English knowledge.

Nice to have:

  • Familiarity with BI tools like Tableau, Looker, or Power BI is a plus.
  • 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.

Are you a technically skilled, hands-on engineer that's passionate about data engineering? Join us at SEON and explore the opportunity to join a world-class research and development organization that is also passionate about creating great data experiences for our software engineers. Those great experiences ensure that we can deliver amazing solutions to the customers that we are obsessed with

SEON provides an API-first solution that helps our customers (many of the world's leading providers of digital experiences in financial services, insurance, entertainment, etc) defend their customers from Fraud and Financial Crimes. With over 250 Fraud Fighters across four global offices (Austin, Budapest, London, and Jakarta), our goal remains unwavering: to make the internet a safe place for businesses and customers to transact. Our achievements, including a record-breaking Series B funding round and recognition in TechCrunch, has led to recognition as the World's quickest-growing fraud prevention company. We take pride in our rapid growth and our mission to democratize fraud-fighting while empowering the best online businesses. Join us in our journey to make the internet a safer space for everyone.

What we offer: 

  • Employee stock ownership plan (ESOP)
  • Hybrid working environment (3 days in the office per week)
  • Flexible hours
  • Generous Holiday allowance
  • Access to significant opportunities for learning and development
  • Private health insurance, including dependants (inc. employee assistance & mental health support)
  • Complimentary weekly language courses
  • Enhanced Parental leave
  • Monthly company breakfast and weekly Lunch allowance
  • 'Work from anywhere' 60-day remote work
,[ 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.] Requirements: Degree, Data engineering, SQL, Big data, Cloud, Data modeling, Architecture principles, BI tools, Real-time data processing systems, Event-driven architectures, Machine learning, DevOps, CI/CD Tools: GitLab, GitHub, Agile, Scrum. Additionally: Training budget, Private healthcare, Small teams, Lunch card, Employee referral bonus, Employee stock purchase plan, International projects, Mental Health Support, Eye Care, Wellness Days, Parental Leave, Language classes, Home office, Flexible hours, Free coffee, Free snacks, Free beverages, Free lunch, In-house trainings, Modern office, Startup atmosphere, Free breakfast.

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