Data Engineer

Job Posting Organization:
The World Bank Group is a global partnership of five institutions dedicated to ending extreme poverty, increasing shared prosperity, and promoting sustainable development. Established with 189 member countries and over 130 offices worldwide, the organization is one of the largest sources of funding and knowledge for developing countries. The World Bank Group works with public and private sector partners to invest in groundbreaking projects, utilizing data, research, and technology to address urgent global challenges. The organization aims to deliver transformative information and technologies to its staff, enabling them to achieve their mission effectively.

Job Overview:
The Data Engineer position at the World Bank Group is a critical role focused on designing, building, and maintaining the data infrastructure that supports the organization's data-driven decision-making processes. This position requires a proactive approach to developing ETL processes, optimizing data retrieval performance, and collaborating with various stakeholders to gather and understand data requirements. The Data Engineer will play a pivotal role in supporting the organization's data integration and transformation initiatives, ensuring that the data infrastructure is robust, efficient, and aligned with the organization's goals. The role also involves working within the Information and Technology Solutions (ITS) Vice Presidential Unit, which is dedicated to advancing the Bank's digital transformation and fostering a culture of responsible innovation. The Data Engineer will be expected to contribute to the development of data pipelines, support federated data architecture, and enable domain teams to manage their data autonomously while adhering to enterprise standards.

Duties and Responsibilities:
The Data Engineer will be responsible for a wide range of duties, including but not limited to:

• Data Pipeline Development: Designing, developing, and maintaining data pipelines for ingestion, transformation, and serving across batch and streaming workloads. Building ETL/ELT workflows to integrate data from diverse sources into enterprise data platforms. Developing data transformation logic using technologies such as Apache Spark, PySpark, SparkSQL, and SQL. Implementing change data capture (CDC) patterns for real-time data synchronization.
• Federated Data Pipelines & Domain Enablement: Supporting federated data pipeline architecture that allows Line of Business (LOB) teams to manage their domain data. Contributing to self-serve data infrastructure that abstracts complexity for domain teams.
• Templates, Blueprints & Patterns: Developing reusable pipeline templates and Infrastructure as Code (IaC) patterns for common data product types. Creating blueprints for data ingestion, transformation, quality validation, and serving.
• Data Integration: Integrating data from multiple internal and external sources into unified data assets. Building reusable data integration patterns and connectors.
• Data Quality & Testing: Implementing data quality checks, validation rules, and automated testing within pipelines.
• Data Observability & Operations: Implementing logging, monitoring, and alerting for pipeline health and performance.
• Analytics & AI Enablement: Building data pipelines that enable analytics, reporting, and business intelligence use cases.
• Collaboration & Enablement: Partnering with data architects and collaborating with business analysts and data scientists.
• Coaching & Technical Mentorship: Supporting data engineering delivery with contractor and consultant teams. 1
• Continuous Improvement: Assisting in evaluating emerging data engineering technologies and identifying opportunities for enhancement.

Required Qualifications:
The ideal candidate for the Data Engineer position should possess a combination of technical skills and capabilities, including:

• Proficiency in Data Modeling, Data Structure and Algorithms, Business Intelligence, and Data Integration.
• Advanced skills in DevOps, Data Lake Architecture, and Databricks.
• Strong business acumen and understanding of the Product Development Life Cycle.
• Ability to influence others and work within a Scaled Agile Framework (SAFe).
• Experience with data engineering practices and principles, including workflow management and automation.

Educational Background:
Candidates typically require a master's degree with at least 5 years of relevant experience or a bachelor's degree with a minimum of 7 years of relevant experience. Equivalent combinations of education and experience may also be considered. Recommended certifications include SAFe PO/PM and industry certifications in Data Engineering, Data Analytics, and Platform Architecture and Integration.

Experience:
The position requires a significant level of experience, typically 5 years for candidates with a master's degree or 7 years for those with a bachelor's degree. Experience should be relevant to data engineering, including designing and implementing data pipelines, working with data integration, and ensuring data quality and reliability.

Languages:
The mandatory language for this position is English. While no additional languages are specified as preferred, proficiency in other languages may be beneficial in a diverse workplace.

Additional Notes:
This position is a local recruitment opportunity with a term duration of 4 years. The World Bank Group offers comprehensive benefits, including a retirement plan, medical, life and disability insurance, and paid leave, including parental leave. The organization is committed to being an equal opportunity and inclusive employer, ensuring that all individuals are treated fairly and without discrimination based on gender, gender identity, religion, race, ethnicity, sexual orientation, or disability.