Associate IT Officer, Data and Information Management (Associate Data Engineer) - req38607

IFC - International Finance Corporation; Washington (District of Columbia); On-site; USD 130,000 - 180,000; Full time

Job summary

IFC, the International Finance Corporation, is seeking an Associate IT Officer, Data and Information Management with a focus on data engineering in Washington, DC. The role emphasizes leading data products end-to-end, establishing data contracts, and modernizing legacy pipelines using Databricks and AI-assisted techniques.

You will contribute to scalable data platforms and collaborate with cross-functional teams to drive analytics, AI readiness, and operational excellence across IFC's data

Qualifications

• Experience designing and delivering scalable data products.
• Strong programming in Python, SQL, and PySpark.
• Hands-on experience with Databricks lakehouse and AI-enabled workflows.

Responsibilities

• Design, build, and maintain scalable data pipelines using Python, SQL, PySpark.
• Lead ETL and ELT solutions for structured and unstructured data with AI-ready prep.
• Develop data models and lakehouse layers optimized for analytics and reporting.
• Establish data contracts with schemas, ownership, SLAs, and change management.
• Set direction for data products and align with enterprise architecture.
• Modernize legacy workloads onto the Databricks lakehouse and use AI tools to speed work.

Skills

Python

SQL

PySpark

Databricks

Data modeling

ETL/ELT

AI/GenAI

Git

Tools

Databricks

Azure Data Factory

Job description

Associate IT Officer, Data and Information Management (Associate Data Engineer)

Job #: req38607

Organization: IFC

Sector: Information Technology

Grade: GF

Term Duration: Open-Ended Staff (OPEN-OP)

Recruitment Type: International Recruitment

Location: Washington, DC,United States

Required Language(s): English

Closing Date: 10/22/2026 (MM/DD/YYYY) at 11:59pm UTC

Description

At the International Finance Corporation (IFC), a member of the World Bank Group (WBG), you’ll join a diverse, global community working across cultures, disciplines, and borders to address the world’s most pressing development challenges. With 1.2 billion young people reaching working age in the decade ahead, the challenge of job creation has never been greater. Through partnerships across 145 countries and more than 182 offices worldwide, we work with governments, private sector, development partners and other stakeholders to invest in people, strengthen markets, and deliver scalable, data-driven solutions that generate more and better jobs and improve lives. In fiscal year 2026, IFC committed a record $105.6 billion to private companies and financial institutions in developing countries. For more information, visit www.ifc.org.

The Corporate Information Technologies Department enables IFC’s strategic priorities and operations through secure, reliable technology solutions. CIT partners with the business to automate processes, improve responsiveness and efficiency, manage risk, and strengthen data, analytics, information, knowledge, and learning capabilities.

CITDE is IFC’s data solutions organization, building trusted data foundations, scalable platforms, and data products that power decisions, analytics, AI, and operational excellence. We combine modern engineering, product thinking, and business impact to solve institution-wide challenges, accelerate innovation, and create measurable value across global development programs.

We are looking for an experienced Data Engineer to lead the design, delivery, and evolution of trusted data products that support critical business decisions across IFC. This is a senior individual contributor role that combines deep, hands-on data engineering expertise with meaningful data product ownership responsibilities.

The role is anchored in data engineering with some elements of product management. The successful candidate will clarify business intent, shape priorities, define acceptance criteria, make informed trade-offs, and remain accountable for the reliability, adoption, cost, and continuous improvement of assigned data products.

The role also requires hands-on use of AI-enabled engineering practices and a willingness to keep experimenting, learning, and helping the team adopt effective approaches responsibly. Candidates should be able to show how they already use AI assistants or agents in real engineering work, in their current role or in their own projects, and how they check the results. Extensive experience building agentic workflows is not required, but candidates should demonstrate sound judgment, active learning, and openness to changing how data products are designed, built, tested, released, and operated.

Data products in this team serve two kinds of consumers: people, through reports and analysis, and AI agents and natural-language tools that query data directly. The role builds for both.

What success looks like in the first 12 months

• Own at least one data product end to end, with a published contract, quality rules, defined users and measured adoption.
• Move at least one workload off a legacy platform or pattern onto the Databricks lakehouse, using AI-assisted methods where they speed up the work.
• Add reusable specifications, prompts, skills or patterns to the team's shared library, so other engineers can repeat what worked.
• Show measurable improvement in the quality, freshness or cost of the products owned.

Duties And Accountabilities

Data Engineering and Architecture

• Design, build, and maintain scalable, secure, and reliable batch and streaming data pipelines using Python, SQL, PySpark, and modern data processing frameworks.
• Lead ETL and ELT solutions for structured, semi-structured, and unstructured data, including metadata enrichment and AI-ready preparation for analytics and GenAI use cases.
• Develop logical and physical data models, curated datasets, and lakehouse layers optimized for analytics, reporting, operational use, and downstream consumption.
• Establish and evolve data contracts covering schemas, definitions, ownership, service levels, quality expectations, and change-management arrangements.
• Set technical direction for assigned data products and ensure alignment with approved enterprise architecture patterns and standards.
• Analyze schema changes and downstream impacts, align solutions with master and reference data, and guide decisions on versioning and migration.
• Review designs and code, resolve complex engineering issues, and ensure solutions are reusable, maintainable, and fit for production.
• Modernize legacy data workloads (for example Oracle Exadata, Informatica, and Azure Data Factory pipelines) onto the Databricks lakehouse, including analysis of existing logic, reconciliation of old and new outputs, and controlled cutover. Use AI tools to speed up code analysis, conversion, and test generation for this work.
• Apply modern engineering practices on Databricks, including Git-based development, Databricks Asset Bundles or