Job Description

Roles & Responsibilities

CO-LEAD IMPACT'S DIGITAL DATA TRANSFORMATION INITIATIVES

DESIGN, IMPLEMENT AND MAINTAIN SCALABLE DATA PIPELINES AND DATA STORAGE INFRASTRUCTURE

ENSURE HIGH-QUALITY, RELIABLE AND REUSABLE DATA PIPELINES

OPERATIONALIZE, MONITOR AND OPTIMIZE DATA PROCESSES

DEFINE AND IMPLEMENT DATA STANDARDS AND BEST PRACTICES ACROSS MISSIONS

ADDTIONAL TASKS (ON AN AD-HOC, BY NEED BASIS)

Desired Candidate Profile

QUALIFICATIONS & EXPERIENCE

Master s degree or higher in a relevant discipline (e.g., Computer Science, Data Science, Statistics, Econometrics, or related fields), or equivalent knowledge acquired through self-learning and/or previous professional experience in data engineering or data science
At least 5 years of relevant work experience, preferably in the humanitarian or development sector

Technical Knowledge & Skills

Proven ability to design, implement, maintain, and optimize centralized data storage solutions and scalable data processing workflows
Strong passion for data engineering and data science challenges, with a focus on building efficient, reliable, and maintainable solutions
Advanced working knowledge of Python, R and SQL
Solid experience with relational databases and ETL
Experience implementing and maintaining CI/CD pipelines and applying coding best practices (unit testing, logging, version control, ...)

Soft skills

Strong analytical and problem-solving skills with attention to detail and commitment to producing high quality work
High level of autonomy and initiative, able to independently drive tasks and proactively propose innovative technical solutions.
Ability to communicate clearly and effectively with team members, including when facing technical challenges.
Openness to feedback, continuous learning, and knowledge sharing.
Adaptability and flexibility to thrive in a fast-paced, results-oriented environment, including remote and cross-country collaboration.
Fluency in English

DESIRED

Experience with cloud computing platforms and services, preferably Azure,
Experience in Python-based data engineering workflows, including libraries and frameworks such as data load tool (dlt), SQLModel, SQLMesh, dbt, Airflow or similar tools for building, automating, orchestrating, and monitoring data pipelines
Experience with KoboToolbox, focusing on interaction via the API and understanding the various data structures stored on the server and accessible through the API.
Knowledge or experience in developing data-oriented web interfaces or dashboards
Experience defining, promoting, and supporting adoption of technical standards and best practices across teams and country missions
Awareness of emerging technologies and trends in data engineering and data science, and capacity to assess their applicability to organizational needs
Good understanding of statistics and standard machine learning algorithms (supervised and unsupervised)
Fluency in French and/or Spanish
Familiarity with the humanitarian aid system

Data Engineering Specialist
IMPACT Initiatives

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