IMF
DataEngineer/Sr.DataEngineer-ITDDP(Contractual)
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“Data Engineer/Sr. Data Engineer -ITDDP (Contractual) at IMF. Skills: Azure cloud platform management, Data pipeline engineering, Data storage platform operation, Data governance enablement, DevOps and automation, Self-service analytics support, Performance monitoring and optimization, Cost efficiency driving. Operating and improving the enterprise data platform. Delivering analytics solutions”
What You'll Achieve.
Deliver scalable, secure, business-aligned capabilities; Proven delivery of complex analytics solutions; Effective delivery of service provider resources; Ensure optimal networking, storage, compute, and identity functions; Ensure compliance with enterprise security and regulatory requirements; Ensure consistency between physical and logical models; Ensure optimal performance and usability of data models
Industry & Context.
Analyzes requests, designs methodology and develops programs and modules for advanced data modeling visualization
One-year contractual appointment, Contractual appointments at the IMF are renewable for up to four years of cumulative contractual service, pending incumbent's performance, budget availability and continuous business need
What They're Looking For.
Must Have
Azure certifications (Administrator, Data Engineer, or Architect tracks), 5 to 6 years in Azure cloud and data engineering roles, Experience with Azure Purview or equivalent data governance tools, Hands-on experience with at least one target architecture: Medallion, Data Mesh, Semantic Layer–First, Familiarity with Event-driven architectures, Familiarity with API-based data sharing, Familiarity with Real-time analytics, Experience with CI/CD pipelines (Azure DevOps, GitHub Actions), Experience with Infrastructure as Code, 5 to 6 years of technical architect experience directly related to Azure Cloud development and administration, Demonstrated technical expertise of working with tools/services such as Power BI, Oracle PL/SQL (among others) and Azure Functions
Nice to Have
Semantic Layer–First Architecture
What You'll Do.
Operating and improving the enterprise data platform
Delivering analytics solutions
Designing and running data warehouse solutions
Coordinating service provider resources
Provisioning Azure resources
Enforcing RBAC and policies
Monitoring Azure health
Controlling Azure costs
Building and maintaining scalable ETL/ELT workflows
and lakehouse environments
Enforcing access controls
and compliance standards
Automating deployments and platform operations using CI/CD and Infrastructure as Code
Delivering curated datasets
Optimizing semantic models
Enabling governed BI usage
Tracking pipeline reliability
and query performance
Optimizing compute/storage usage
Implementing cost management strategies
Designing and managing a multi-layered data architecture
Building and orchestrating pipelines using Azure Data Factory
Enforcing data quality and schema evolution controls
Optimizing storage and compute for high-throughput batch and streaming ingestion
Implementing partitioning
and Delta optimization strategies
Developing self-service analytics
Designing and managing enterprise semantic models
Enabling self-service analytics through governed datasets
Optimizing data models for performance and usability
Integrating semantic layer with upstream pipelines
Ensuring consistency between physical and logical models
Conducting Azure Cloud Administration
Production deployments
Managing corporate data azure infrastructure
Monitoring platform health using Azure-native observability tools
Ensuring compliance with enterprise security and regulatory requirements
Supporting data governance enablement using metadata management tools (Collibra and Purview)
and data lineage capabilities of metadata management tools
Enforcing data classification
and data quality standards
designing methodology and developing programs and modules for advanced data modeling visualization
Leading Managed Service Providers ensuring delivery of data driven solutions
How You'll Work.
Team & Collaboration
Partnering with platform owners; Collaboration with the enterprise architects; Collaboration with source platform teams; Collaboration with other integrated team members; Collaboration with enterprise Azure platform support
Communication Scope
oral and written communication skills; ability to convey higher level technical concepts to non-experts
Full Job Description
Work for the IMF. Work for the World. **Job Summary** Under the direction of the Deputy Division Chief (Data Platforms Division) in the IT Department at the IMF, the Data Engineer/Sr. Data Engineer supports the Corporate Data team by operating and improving the enterprise data platform and delivering analytics solutions. The role partners with platform owners to design and run data warehouse solutions, reports, and dashboards, and coordinates service provider resources for effective delivery. This role blends cloud platform engineering, data pipeline development, and data governance enablement to deliver scalable, secure, business-aligned capabilities. It requires proven delivery of complex analytics solutions, strong Azure/cloud and data warehousing skills, and experience implementing and supporting data governance tools. **The ideal candidate should demonstrate expertise and capability to:** * **Manage Azure cloud platform:** provision resources, enforce RBAC and policies, secure networking, monitor health, ensure backup/DR, and control costs. * **Engineer data pipelines:** build and maintain scalable ETL/ELT workflows for batch and real-time data ingestion and transformation. * **Operate data storage platforms:** manage data lakes, warehouses, and lakehouse environments with performance optimization. * **Enable data governance:** enforce access controls, data classification, quality checks, lineage, and compliance standards. * **Implement DevOps and automation:** use CI/CD and Infrastructure as Code to automate deployments and platform operations. * **Support self-service analytics:** deliver curated datasets, optimize semantic models, and enable governed BI usage. * **Monitor and optimize performance:** track pipeline reliability, data latency, and query performance with alerting and tuning. * **Drive cost efficiency:** optimize compute/storage usage and implement cost management strategies. **Major Duties and Responsibilities** 1\. Design and manage a multi-lay
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