Data Scientist / Data Engineer

AIT Global, Inc.
United States
3 months ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Business Analytics Applications Data Analysis Microsoft Azure Cloud Computing Information Systems Information Engineering Data Warehousing Decision Support Systems Document-Oriented Databases R (Programming Language)
+17 more
Python (Programming Language) Machine Learning Software Deployment SQL Databases Google Cloud Azure Data Factory Fast Healthcare Interoperability Resources Snowflake Apache Spark Build Management Microsoft Fabric Information Technology AWS Data Analytics Machine Learning Operations Restful APIs Data Pipelines Databricks

Job description

Hands-on data professional responsible for end-to-end data engineering, analytics, and model development for development sector programs. Covers data pipeline architecture, dataset preparation, dashboarding, and analytics workflow deployment. Engagement Details:

  • Location: Home-based, remote. No office attendance required.
  • Engagement type: Independent consultant or sub-contractor under company.
  • Duration: Level of Effort basis per task order. Initial bench placement is for 12 months with extensions possible.
  • Travel: Only when a specific task order requires it. All travel pre-approved and reimbursed., * Design and build data pipelines, data warehouses, and analytics platforms supporting development programs.
  • Prepare, clean, and transform datasets from country information systems, surveys, administrative records, and external sources.
  • Develop analytics models, dashboards, and reporting layers for program monitoring, evaluation, and decision support.
  • Build and deploy machine learning models in production environments, including MLOps practices for model monitoring and retraining.
  • Work with cloud platforms such as Azure, AWS, Google Cloud Platform and open-source data stacks to deliver scalable analytics workflows.
  • Document data flows, lineage, and governance controls for donor reporting and compliance.

Requirements

  • Bachelor’s degree required in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field. Master’s degree preferred.
  • Minimum 7 years of relevant professional experience, with 5 to 10 plus years specifically in data engineering, analytics, or model development.
  • Proficiency with Python, R, SQL, REST APIs, cloud platforms, and modern data pipeline architectures including dbt, Airflow, Spark, Databricks, or Microsoft Fabric.
  • Demonstrated experience preparing datasets, dashboards, models, or analytics workflows for production deployment.
  • Familiarity with health, education, or social sector data standards preferred, including DHIS2, FHIR, CSPro.
  • Experience working in low and middle income countries or public sector environments preferred.

Preferred Certifications:

  • Azure Data Engineer
  • AWS Data Analytics Specialty
  • Databricks or Snowflake
  • CAP (Certified Analytics Professional)

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