Senior/Economic Data Systems Engineer

Job Posting Organization:
The International Monetary Fund (IMF) is an international organization established in 1944 with the mission to promote global monetary cooperation, secure financial stability, facilitate international trade, promote high employment and sustainable economic growth, and reduce poverty around the world. The IMF has a diverse workforce of over 2,700 employees from more than 150 countries, operating in various regions to provide financial assistance and policy advice to its member countries. The organization plays a crucial role in the global economy by providing financial resources, technical assistance, and policy advice to help countries achieve macroeconomic stability and sustainable growth.

Job Overview:
The Senior/Economic Data Systems Engineer position at the IMF is a critical role that focuses on providing comprehensive economic data engineering services across the organization. The incumbent will be responsible for the design, implementation, modernization, and operation of economic data systems that support various functions such as surveillance, lending, capacity development, research, analytics, reporting, and AI-enabled use cases. This role requires a deep understanding of the full data lifecycle, including source acquisition, ingestion, transformation, quality validation, metadata management, semantic modeling, dissemination, visualization, and monitoring. The engineer will work collaboratively with a range of stakeholders, including economists, financial experts, data owners, and application teams, to assess requirements, design solutions, and ensure reliable production operations. The position emphasizes the importance of engineering robust, secure, scalable, and governed economic data systems using advanced data engineering practices and contemporary technologies.

Duties and Responsibilities:

• Provide advanced engineering expertise in coordination with solution owners, product owners, project managers, enterprise architects, technical leads, data owners, security" style="border-bottom: 1px dotted #007bff !important;">security stakeholders, and platform administrators to enhance and modernize economic data systems while adhering to enterprise architecture, governance, security, and technology policies.
• Design, implement, enhance, and operate economic data systems across acquisition, ingestion, transformation, storage, quality validation, semantic modeling, visualization, dissemination, monitoring, and lifecycle management.
• Apply general architecture patterns for governed economic data solutions, including reusable data products, domain-oriented data models, environment separation, curated data layers, secure integration boundaries, metadata-driven design, and operational support models.
• Engineer source onboarding and data integration patterns, including batch, streaming, change data capture, file-based exchange, API integration, schema onboarding, data contracts, metadata capture, ingestion error handling, and secure credential and connectivity practices.
• Develop data transformation, storage, and processing solutions using SQL, Python, cloud-native data services, lakehouse or warehouse platforms, NoSQL and search technologies, and enterprise analytics tools as appropriate to the business and technical requirements.
• Implement data quality engineering controls including validation rules, reconciliation logic, freshness and completeness checks, anomaly thresholds, quality dashboards, exception handling, and evidence that data is fit for downstream consumption and promotion.
• Implement DataOps and DevOps practices including source control, automated testing, CI/CD, controlled Dev/Test/Prod promotion, deployment documentation, release checklists, rollback planning, production readiness reviews, and lifecycle controls.
• Configure, manage, monitor, and tune installed economic data systems, data platforms, pipelines, semantic models, access controls, capacities, and associated infrastructure to ensure availability, scalability, performance, reliability, security, and cost-effective production operations.
• Perform technical investigation, incident triage, root-cause analysis, remediation, and post-incident prevention for failures, data quality issues, performance anomalies, SLA or OLA breaches, and operational defects affecting economic data products and systems. 1
• Implement governance and compliance controls including metadata completeness, lineage, classification, access management, privacy protections, privileged access controls, audit evidence, retention considerations, data stewardship support, and exception tracking in accordance with enterprise standards. 1
• Support AI, machine learning, data science, semantic search, retrieval-augmented generation, forecasting, and AI-assisted economic research by engineering trusted, traceable, well-governed, secure, and reusable economic data assets; advise application development, analytics, and data engineering teams on economic data standards, SDMX, semantic definitions, tools, and reusable engineering patterns; and provide guidance to junior colleagues as needed. 1
• Ensure platform’s high availability. Monitor system performance, uptime, and resolve major technical escalations. Oversee infrastructure costs, storage limits, and service provider performance. 1
• Act as the bridge between technical engineers and business stakeholders. Manage the platform roadmap and feature backlog for platform enhancements.

Required Qualifications:
The position requires a Bachelor’s degree in computer science, Computer Engineering, Software Engineering, Electrical Engineering, Information Systems, Data Engineering, or a related discipline, along with ten (10) years of relevant professional experience. Alternatively, a Master’s degree with a minimum of four (4) years of relevant professional experience is acceptable. Candidates must have advanced experience in designing, implementing, enhancing, and operating enterprise-scale data engineering systems, preferably in economic, financial, statistical, institutional, or time-series data domains. A strong knowledge of economic data, metadata and semantic models, SDMX, financial and economic metadata standards, and modern data architecture and engineering practices is essential. Hands-on proficiency in SQL and Python, along with experience with relevant data platforms, databases, APIs, orchestration tools, streaming technologies, cloud-native services, open data formats, search technologies, and analytics tools such as Microsoft Fabric, Power BI, Databricks, Spark, Snowflake, and BigQuery is required. Candidates should also have experience applying engineering and operational practices, including source control, automated testing, CI/CD, controlled environment promotion, release and rollback management, performance optimization, incident response, access controls, privacy protections, and auditability.

Educational Background:
Candidates must possess a Bachelor’s degree in a relevant field such as computer science, Computer Engineering, Software Engineering, Electrical Engineering, Information Systems, Data Engineering, or a related discipline. A Master’s degree in one of these fields is preferred and can substitute for some of the required experience.

Experience:
The position requires a significant level of experience, specifically ten (10) years of relevant professional experience for candidates with a Bachelor’s degree, or a minimum of four (4) years of relevant professional experience for those with a Master’s degree. This experience should include advanced knowledge and hands-on proficiency in enterprise-scale data engineering systems, particularly in economic, financial, statistical, institutional, or time-series data domains.

Languages:
Proficiency in English is mandatory, as it is the working language of the IMF. Knowledge of additional languages is considered a plus, as it can enhance communication with diverse stakeholders and contribute to a more inclusive work environment.

Additional Notes:
This vacancy is a 3-year Term appointment in accordance with the Fund’s new employment rules that took effect on May 1, 201

• The position is classified at levels A11 and A12, indicating a seniority level that requires significant expertise and experience. The IMF is committed to diversity and inclusion in its workforce and welcomes requests for reasonable accommodations for disabilities during the selection process. Information on how to request accommodations will be provided during the application process.