Data Engineer

At Satori Analytics, we aim to change the world one algorithm at a time by bringing clarity to global brands thought Data & AI. From cloud-based ecosystems for fintech to predictive models for airlines, our cutting-edge solutions cover the entire data lifecycle—from ingestion to AI applications.

As a fast-growing scale-up, our team of 100+ tech specialists—including Data Engineers, Data Scientists, and more—delivers innovative analytics solutions across industries like FMCG, retail, manufacturing and FSI. Join us as we lead the data revolution in South-Eastern Europe and beyond!

We're looking for a Data Engineer to design, build, and operate the scalable data platforms behind global payments & financial services leader's marketing products. You'll enable campaign measurement, customer insights, reporting, and AI/ML initiatives — partnering with Product, Engineering, Data Science, and Business stakeholders to turn complex data challenges into secure, reliable, high-quality solutions at enterprise scale.

• Independently design and maintain scalable ETL pipelines within a collaborative project team, delivering clean, analytics- and AI-ready data
• Work with SQL, Python, PySpark and tools like MS Fabric, Azure Data Factory, Databricks, Snowflake to develop, optimize, and automate data processes
• Design robust ETL, scalable data models and optimised design patterns for analytics and BI workloads
• Ensure data quality and data governance through automated checks, monitoring, source to target mapping, data lineage and continuous improvements
• Collaborate with cross-functional teams to understand data requirements, business semantics and deliver high-quality solutions
• Troubleshoot, optimize, and support production pipelines to keep data flowing smoothly
• Use Git and Agile practices to work effectively in collaborative, iterative projects

• BSc or MSc degree in Computer Science, Software Engineering, Data Science, or any relevant field.
• Minimum 3 years of experience designing and building scalable data platforms and distributed data-processing solutions.
• Strong expertise across 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 modelling, 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, plus the judgement to balance technical excellence with business priorities.