ICT Specialist - Data Engineering (Open Externally)
Organizational Context
The Information and Communication Technology Section (ICTS) at UNV supports digital transformation through cloud platforms, business applications, data services, and cybersecurity. The ICTS Data Team specifically focuses on developing and maintaining enterprise data pipelines, models, and analytics products to enable evidence-based decision-making. This role provides technical leadership and expertise to enhance UNV's enterprise data platform.
Job Purpose
The ICT Specialist - Data Engineering will serve as a lead technical resource for UNV's enterprise data engineering function. This role is responsible for providing expert guidance on data architecture, platform design, integration strategies, and governance frameworks. The purpose is to strengthen UNV's enterprise data platform by ensuring data from various sources is integrated, governed, and made available for reliable reporting, analytics, and AI/ML use cases. The specialist will drive platform modernization, implement DataOps practices, and enable analytics capabilities, contributing to data-driven decision-making across the organization. This position offers technical authority through guidance and advisory services rather than direct supervision.
Responsibilities
Provide technical leadership and subject matter expertise in enterprise data platform architecture, design, and evolution. Develop and optimize scalable ETL/ELT workflows for data ingestion, transformation, and loading from diverse sources. Design and enhance data models (dimensional, normalized, semantic) to support reporting and analytics. Implement data quality, governance, lineage, and compliance frameworks. Develop and maintain CI/CD pipelines for data engineering code, including automated testing and deployment. Support the design, development, and optimization of BI solutions, reports, and dashboards. Engage with stakeholders to define data needs, resolve issues, and promote a data-driven culture. Manage and guide external vendor consultants and technical resources for data initiatives, ensuring quality and timely delivery of solutions.
Work Experience
A minimum of five years of relevant professional experience with a Master's degree, or seven years with a Bachelor's degree, is required. Experience should encompass data engineering, cloud data platforms, business intelligence, data management, DevOps/DataOps, or analytics engineering.
Skills
Advanced SQL and Python/PySpark; Azure Data Factory or equivalent ETL/ELT tools; Databricks, Delta Lake, Azure SQL, data lakes, warehouses, or lakehouse architecture; Data quality, validation, metadata, lineage, and governance implementation; CI/CD and version control for data solutions; Power BI semantic models, dashboards, and reporting support; Data integration, transformation, and engineering; Data modelling and analytics enablement; DataOps, automation, and observability.