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Satori Analytics is a fast-growing scale-up of 100+ tech specialists delivering innovative data and AI solutions across industries including FMCG, retail, manufacturing, and financial services. The company operates cloud-based ecosystems and predictive models for global brands, covering the entire data lifecycle from ingestion to AI applications.
In this Data Engineer role, you will design, build, and operate scalable data platforms supporting a global payments and financial services leader's marketing products. You'll enable campaign measurement, customer insights, reporting, and AI/ML initiatives by partnering with Product, Engineering, Data Science, and Business stakeholders to transform complex data challenges into secure, reliable, enterprise-scale solutions.
Day-to-day responsibilities include:
- Independently design and maintain scalable ETL pipelines within collaborative project teams, delivering clean, analytics- and AI-ready data
- Work with SQL, Python, PySpark, and tools such as MS Fabric, Azure Data Factory, Databricks, and Snowflake to develop, optimize, and automate data processes
- Design robust ETL pipelines, scalable data models, and optimized design patterns for analytics and BI workloads
- Ensure data quality and governance through automated checks, monitoring, source-to-target mapping, data lineage, and continuous improvements
- Collaborate with cross-functional teams to understand data requirements and business semantics
- Troubleshoot, optimize, and support production pipelines
- Use Git and Agile practices in collaborative, iterative projects
The role offers a hybrid working model based in the modern Athens office with flexibility to work remotely from anywhere in the European Economic Area (EU, Switzerland) or UK for up to 6 weeks per year. Benefits include competitive salary, private health insurance, top-tier tech gear, learning and development budget (certifications through Microsoft, AWS, Salesforce, Databricks), career growth opportunities, and a collaborative team environment.
REQUIREMENTS:
- BSc or MSc degree in Computer Science, Software Engineering, Data Science, or relevant field
- Minimum 3 years of experience designing and building scalable data platforms and distributed data-processing solutions
- Strong expertise in modern data engineering technologies: Spark, Kafka, Hadoop ecosystem tools, cloud-native data services, and large-scale processing frameworks
- Proficiency in one or more of Python, Java, Scala, or SQL
- Deep understanding of data modeling, ETL/ELT design patterns, data architecture, and data lifecycle management with a track record building pipelines for analytics, reporting, ML, and operational data products
- Hands-on experience delivering on cloud platforms such as Databricks, AWS, Azure, or GCP
- Solid grasp of data governance, security, privacy, lineage, metadata management, and regulatory compliance
- Experience with CI/CD, DevOps automation, infrastructure-as-code, and observability frameworks
- Strong problem-solving skills for diagnosing complex issues in distributed environments and balancing technical excellence with business priorities
