Data Engineer

at  The United Nations Industrial Development Organization UNIDO

Requisition ID: 4106
Grade: ISA Specialist
Country: Austria
Duty Station: Vienna
Category: International Consultant
Type of Job Posting: Internal/External
Employment Type: NonStaff-Regular
Application Deadline: 05-Jul-2024, 11:59 PM (CEST)

EDUCATION

Advanced university degree (master’s or equivalent) in one or more of the following areas: information technology, business administration, digital technologies, or related fields is required.
PMP or similar project management certifications, reflecting a strong foundation in leading and managing complex projects with cross-functional teams is desirable.

EXPERIENCE

• A minimum of three (3) years of practical experience in backend development and data engineering, is required.
• Proficiency in backend programming languages such as Java, Python, and experience with backend frameworks is required.
• Demonstrated experience in designing and developing robust data pipelines for real-time and batch data processing, with a strong emphasis on efficiency and scalability is required.
• Solid understanding of data governance principles, including metadata management, data quality, and data security practices, to ensure the integrity and privacy of data across the organization is required.
• Proven expertise in managing SQL and NoSQL databases, including performance optimization and schema design, to support complex data storage and retrieval needs is required.
• Experience with DevOps and MLOps methodologies, including continuous integration and deployment (CI/CD) and the management of machine learning models in production environments, to enhance operational efficiency and model reliability is desirable.
• Familiarity with cloud services (e.g., AWS, Azure, GCP) and the deployment of data infrastructures in cloud environments, leveraging cloud-native services for scalability and resilience is desirable.
• Basic understanding of frontend development technologies (e.g., Angular, React) to facilitate effective collaboration with frontend developers and integration of backend services with user-facing applications is desirable.
• Experience with data visualization tools like PowerBI and Tableau, to develop actionable insights from data and support business intelligence efforts is desirable.
• Basic knowledge of AI and machine learning concepts, to support the development and deployment of data science projects and contribute to the organization’s AI initiatives is desirable.

Under the supervision and guidance of the Chief of COR/DIG, the senior data engineer will be responsible for implementing comprehensive digital transformation across our organization. This role involves leveraging innovative technologies and methodologies to enhance business processes, customer experiences, and organizational efficiency.

Key functions:

• Backend Development and Data Systems Integration: Design and implement scalable backend services and APIs for data ingestion, processing, and distribution, ensuring seamless integration with existing web systems and databases.
• Data Pipeline Architecture: Build and maintain robust data pipelines for real-time and batch data processing, supporting analytics, machine learning models, and business intelligence tools.
• DevOps/MLOps Practices: Implement DevOps practices for continuous integration and deployment (CI/CD) of data-driven applications and MLOps frameworks to streamline the lifecycle of machine learning models, from development to production.
• Data Governance and Quality Control: Establish and enforce data governance frameworks to ensure data quality, consistency, and security across the organization, incorporating best practices in metadata management, data modeling, and lineage.
• Infrastructure and Cloud Management: Oversee the deployment and management of data infrastructure in cloud environments (e.g., AWS, Azure, GCP), leveraging serverless architectures, containerization (e.g., Docker, Kubernetes), and managed services for scalability and efficiency.
• Collaboration and Strategic Advisory: Work closely with IT, data science, and business teams to align data engineering initiatives with organizational goals, providing strategic insights on leveraging data for decision-making and innovation.
• ontinuous Learning and Innovation: Stay informed of the latest trends in data engineering, backend development, and AI/ML technologies, advocating for the adoption of new tools and practices to enhance organizational capabilities