Senior Data Engineer (all genders)

At PRODYNA, we design, implement, and operate modern cloud-native software and data platforms for mid- to large-sized enterprises. We help our customers unlock the value of their data through scalable architectures, advanced analytics, and cloud technologies while delivering future-proof solutions built on Microsoft Azure.

As part of our growing Data Engineering team in Athens, you will design and build enterprise-grade data platforms, modern Lakehouse architectures, and high-performance data pipelines that power analytics and AI workloads. Working closely with architects, software engineers, and cloud specialists, you'll help customers transform complex business requirements into reliable, scalable, and secure data solutions.

Your tasks

• Design, build and maintain scalable batch and streaming data pipelines using Python, Apache Spark and Azure Databricks. Design, build and maintain scalable batch and streaming data pipelines using Python, Apache Spark and Azure Databricks.
• Develop modern ETL/ELT architectures capable of processing large-scale enterprise datasets.
• Design and implement Lakehouse solutions using Delta Lake and other modern table formats.
• Build robust APIs and data services for internal and external consumers.
• Optimize Spark applications through performance tuning, partitioning strategies and bottleneck analysis.
• Implement dimensional data models, Slowly Changing Dimensions (SCD), schema evolution and data quality controls.
• Develop real-time streaming solutions using Spark Structured Streaming.
• Collaborate with Cloud Architects and Software Engineers to design end-to-end Azure-based data platforms.
• Build Infrastructure as Code using Terraform/Terragrunt and support CI/CD automation.
• Ensure observability through logging, monitoring and operational metrics.
• Apply security best practices including encryption, secrets management and protection of sensitive data.
• Participate in customer workshops, architecture discussions and technical consulting activities.  

Your profile

• 6+ years of professional experience in Data Engineering.
• Proven experience designing enterprise-scale data platforms.
• Deep expertise in Spark performance optimization.
• Strong experience with streaming architectures and Spark Structured Streaming.
• Experience with Lakehouse technologies such as Delta Lake, Apache Iceberg or Apache Hudi.
• Advanced knowledge of data modeling, schema evolution and enterprise data architecture.
• Experience implementing Infrastructure as Code using Terraform/Terragrunt.
• Knowledge of observability, monitoring and production operations.
• Strong understanding of security, encryption, key management and GDPR/PII handling.
• Ability to mentor engineers and provide technical leadership.
• Experience working directly with enterprise customers and stakeholders.
• Fluency in English.