Senior Data Engineer

PRODYNA

Design and build enterprise-grade cloud-native data platforms for analytics and AI workloads at PRODYNA. Collaborate with architects and engineers to deliver scalable data solutions in Athens.

Posted 7/14/2026full-timeAthens • 🇬🇷 GreeceSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data platforms and pipelines using Python, Apache Spark, and Azure Databricks. Proficient in implementing ETL/ELT architectures, optimizing performance, and applying security best practices in data engineering.

Highest-signal resume keywords

Python DevelopmentApache Spark / PySparkAzure DatabricksETL/ELT Pipeline DesignInfrastructure as Code (Terraform/Terragrunt)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ModelingREST API DevelopmentStreaming ArchitecturesLakehouse TechnologiesPerformance OptimizationSchema EvolutionData Quality ControlsObservability and MonitoringGDPR/PII Handling

Soft Skills

Strong Communication SkillsCustomer-Oriented MindsetMentoring and Technical Leadership

Tools & Technologies

Azure ServicesGitCI/CD PracticesDelta LakeApache IcebergApache Hudi

Certifications & Qualifications

Professional Data Engineer

Industry Keywords

Cloud-Native SoftwareData PlatformsBatch and Streaming Data PipelinesEnterprise Data ArchitectureSecurity Best Practices

Tech Stack

Tools & technologies

ApacheAzureCloudETLPySparkPythonSparkTerraformVault

About the role

Key responsibilities & impact

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.
- 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.

Requirements

What you’ll need

Professional Data Engineer
- 3+ years of experience in Data Engineering or Backend Engineering.
- Strong Python development skills with good understanding of software engineering principles.
- Experience with Apache Spark / PySpark.
- Hands-on experience with Azure Databricks.
- Experience designing scalable ETL/ELT pipelines.
- Good understanding of relational and analytical data modeling.
- Experience developing REST APIs.
- Familiarity with Azure services (Storage Accounts, Key Vault, Event Hubs, Azure Functions, etc.).
- Experience with Git and CI/CD practices.
- Strong communication skills and customer-oriented mindset.
- Fluency in English.
Senior Data EngineerAdditionally, Senior candidates should demonstrate:
- 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.

Benefits

Comp & perks

**Compensation & Perks**
- Salary: We will settle on the exact compensation amount based on prior experience and skills.
- Private health insurance & Life Insurance from day #1
- Health management scheme (weekly sessions &monthly challenges)
- 25 vacation days
- Team events tech oriented and more
- International network
- Lunch in the office & Go For Eat vouchers
- Employee referral programme/ bonus
**Dedicated budget for:**
- Employee education ~ 800€
- Hardware selection (MacBook or Lenovo ThinkPad) with your own mobile ~ 3000€