Data Engineer

Role summary

The International Rescue Committee (IRC) is a global humanitarian organization working to help people affected by conflict and disaster regain health, safety, education, economic stability, and the ability to shape their own future. Operating in more than 40 countries and 29 U.S. cities, IRC builds solutions that support communities and deliver long-term impact.

Within Technology and Operations, the Data Team creates and maintains the data strategies, systems, and products that power the organization’s global work. The Data Engineer will help implement, configure, and maintain data pipelines and transformation workflows across the IRC data ecosystem, including ELT processes, dbt models, Azure Databricks, and the IRC Lakehouse.

This position is suited to someone with developing to solid experience in dbt, SQL, and Databricks who is ready to take on greater responsibility while working closely with senior engineers and the Data Architect in a collaborative, fast-moving environment.

What you'll do

• Build and support ELT pipelines using Databricks Workflows and Azure Data Factory for scheduled and batch processing from internal and external sources.
• Help bring data from core systems such as D365 CRM and ServiceNow into the Lakehouse.
• Track pipeline runs, investigate failures, and work with senior engineers to resolve issues.
• Contribute to documentation, runbooks, and standard operating procedures for data processes.
• Create and maintain dbt models across staging, intermediate, and mart layers under guidance from senior team members.
• Write dbt tests, assist with source freshness checks, and support data quality practices.
• Apply dbt design principles such as modularity, dependency management, and incremental modeling.
• Partner with analysts and business stakeholders to convert reporting and data needs into dbt models.
• Write intermediate to advanced SQL for extraction, transformation, and validation work.
• Use joins, CTEs, window functions, and aggregations to support reporting and analytics.
• Assist with query tuning and performance troubleshooting in Databricks SQL environments.
• Maintain data models and adapt them as source fields or schemas change.
• Create and support Databricks notebooks and jobs for transformation workloads.
• Build practical experience with Delta Lake and PySpark for data processing.
• Follow Bronze/Silver/Gold Lakehouse design patterns as directed by the Data Architect.
• Assist with cloud resource tasks such as cluster setup and job scheduling.
• Work closely with the Data Team on design, troubleshooting, and delivery.
• Take part in code reviews and use feedback to improve solution quality.
• Document data flows, procedures, and implementation standards.
• Collaborate with Finance, FP&A, Operations, and other business teams to understand data requirements and support delivery.

Requirements

• 3–6 years of practical experience in data engineering, analytics engineering, or a similar technical role.
• Proven background in building or maintaining data pipelines in a professional environment.
• Exposure to cloud data platforms, preferably Azure tools such as Databricks, Data Factory, or Synapse.
• Working knowledge of dbt development, including staging and mart layers.
• Familiarity with dbt testing, documentation, and source configuration.
• Interest in strengthening dbt capabilities, including incremental models and CI/CD integration.
• Experience with Databricks notebooks and basic job or workflow setup.
• Understanding of Delta Lake concepts and Databricks SQL.
• Exposure to PySpark for transformation work.
• Strong SQL ability, including joins, CTEs, window functions, and aggregations.
• Experience using SQL for transformation and validation in a cloud data warehouse.
• Background in ELT pipeline support, monitoring, and basic validation.
• Familiarity with orchestration tools such as Azure Data Factory or Databricks Workflows.
• Basic to intermediate Python skills for scripting, automation, and data processing.
• Understanding of star and snowflake schemas, along with fact and dimension tables.
• Exposure to Lakehouse or medallion architecture is advantageous.
• Curious, proactive, and comfortable solving problems independently and with others.
• Strong communication skills for working across technical and non-technical groups.
• High attention to detail and a strong focus on data quality.
• Comfortable in a collaborative, fast-paced, remote team setting.
• Preferred: experience with Databricks or Azure Synapse Analytics.
• Preferred: familiarity with D365 CRM or similar data structures.
• Preferred: exposure to Git-based workflows and CI/CD for data deployments.
• Preferred: experience in a humanitarian, nonprofit, or international development environment.

Additional information

This role is remote. It reports to the Lead Data Engineer and does not manage any direct reports.

Occasional travel may be required for special projects and on-the-ground learning to support data strategy work.

Professional standards

All IRC staff are expected to follow the IRC Way and its standards for professional conduct: Integrity, Service, Equality, and Accountability. The organization also applies policies covering safeguarding, conflicts of interest, fiscal integrity, reporting wrongdoing, and protection from retaliation. IRC emphasizes preventive action, safe reporting, corrective measures when harm occurs, and team cultures that support critical thinking, shared responsibility, discussion, and objectivity.