Data Platform Engineer
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Bucureşti
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Data Platform Engineer
As a Data Platform Engineer, you will be responsible for designing, building, and evolving scalable data platforms and pipelines that enable enterprise applications, analytics, and AI-driven products.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines, ingestion frameworks, and transformation processes.
- Build and optimise data models to support analytics, reporting, operational systems, and AI use cases.
- Develop robust ETL/ELT solutions to enable efficient and reliable data movement across enterprise platforms.
- Support integration with enterprise data architectures and evolving cloud-based data ecosystems.
- Ensure data solutions align with governance, security, compliance, and enterprise architecture standards.
- Build automated data pipelines to support scheduled and real-time production workloads.
- Deliver production-ready data services, APIs, and reusable data assets for business and engineering teams.
- Implement data quality, validation, and integrity controls through testing, monitoring, and automation.
- Support migration and optimisation of legacy data processes into scalable, enterprise-grade solutions.
- Embed quality assurance practices throughout the data engineering lifecycle, ensuring all deliverables meet Definition of Done standards.
- Contribute to data observability, troubleshooting, incident resolution, and continuous platform improvement.
- Partner with Platform, Full Stack, AI, and business teams to deliver integrated data capabilities.
- Support Agile and sprint-based delivery models, contributing to iterative product development.
- Promote reusable data engineering patterns and engineering best practices across projects.
- Maintain technical documentation and contribute to data governance and operational processes.
Required Skills & Experience:
- Proven experience designing, building, and maintaining enterprise data platforms and data pipelines.
- Strong expertise in ETL/ELT processes, data integration, and data modelling techniques.
- Advanced SQL and Python programming skills.
- Experience with Azure data services, including Azure SQL, Blob Storage, Microsoft Fabric, or equivalent cloud data technologies.
- Experience working with modern data processing frameworks and scalable data architectures.
- Strong understanding of data governance, validation, versioning, and quality management principles.
- Experience delivering production-ready, scalable data solutions.
- Familiarity with APIs and data services integration.
- Knowledge of monitoring, observability, and operational support for data platforms.
Professional Skills:
- Strong analytical and problem-solving capabilities.
- Experience working within Agile delivery frameworks and sprint-based environments.
- Ability to collaborate effectively across engineering, AI, platform, and business teams.
- Excellent communication and technical documentation skills.
- Commitment to continuous learning and adoption of emerging data and AI technologies.
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