Join neXa – Let’s Shape the Future Together!
Position: Data Engineer
At neXa, we’re not just building digital solutions — we’re helping businesses grow smarter. We work with forward-thinking clients across industries to design, build, and implement technology that makes a real difference. From intelligent automation to custom applications, our projects are as diverse as our team.
We’re now looking for a Data Engineer to join a high-energy team building scalable, AI-ready Data Hubs that support analytics, operational reporting, and Generative AI solutions. This role focuses on designing and developing modern cloud-based data platforms capable of handling both batch and real-time data processing across multiple enterprise systems.
You will work closely with architects, AI engineers, and business stakeholders to build reliable, scalable, and high-performance data solutions within a modern Azure and Databricks ecosystem.
Scroll down to see the full job description, including responsibilities and requirements:
Responsibilities:
- Design, develop, and maintain scalable Data Hubs integrating multiple data sources
- Build and optimize ETL/ELT pipelines for ingestion, transformation, and storage of large-scale datasets
- Create logical data models supporting analytical, operational, and AI-driven use cases
- Develop real-time ingestion and streaming data processing solutions Implement data validation, anomaly detection, and monitoring mechanisms
- Optimize data processing, storage, and query performance
- Develop and maintain CI/CD pipelines and automated deployment processes
- Collaborate with data architects, AI engineers, analysts, and business teams
- Ensure scalability, reliability, and maintainability of data infrastructure
- Participate in Agile/Scrum ceremonies and engineering initiatives
- Create and maintain clear technical documentation for pipelines, models, and architecture decisions
- Support continuous improvement and modernization of the data platform ecosystem
Requirements:
- Strong experience in Data Engineering and cloud-based data platforms
- Strong proficiency in Python for data engineering tasks
- Hands-on experience with Azure Data Factory, ADLS, and Azure SQL
- Experience building scalable ETL/ELT pipelines
- Experience with real-time data ingestion and streaming architectures
- Understanding of data preparation for AI/ML and Generative AI solutions
- Experience implementing data quality validation and monitoring mechanisms
- Strong SQL skills for data transformation and analytics
- Experience with Databricks, Apache Spark, and Delta Lake
- Familiarity with CI/CD pipelines and DevOps practices
- Experience with Terraform, Docker, Kubernetes/AKS, and infrastructure automation
- Understanding of data governance, security, and compliance best practices
- Experience working in Agile environments and cross-functional teams
- Strong documentation and communication skills English proficiency at minimum B2 level
Nice to have:
- Experience with Azure Stream Analytics, Event Hubs, or Synapse
- Experience supporting large-scale AI/ML data platforms
- Experience with event-driven and streaming data architectures
- Familiarity with GitHub Actions and Azure DevOps
- Experience with high-volume enterprise data ecosystems
- Experience optimizing distributed data processing systems