Data Engineer

About this role

We are seeking a skilled Data Engineer to design, build, and scale the end-to-end data infrastructure powering analytics, benchmarking, and AI-driven intelligence across higher education ecosystems. This role will own the complete data lifecycle, ensuring scalable, reliable, and AI-ready data solutions for enterprise reporting and intelligent automation.

Roles & Responsibilities:

• Design and implement scalable data lake and data warehouse architectures.
• Build and maintain ETL/ELT pipelines for structured and semi-structured data sources.
• Integrate data from SIS, CRM, LMS, APIs, and external platforms.
• Develop reusable data models for analytics, dashboards, benchmarking, and AI/ML applications.
• Ensure data quality, governance, monitoring, and pipeline reliability.
• Deliver analytics-ready and AI-ready datasets for downstream systems and LLM-based applications.
• Optimize pipeline performance, scalability, and processing efficiency.
• Collaborate closely with Analysts, AI teams, and platform leadership on data initiatives.Lead, mentor, and manage the help desk support team.

Required Skills:

• Strong expertise in SQL, Python, and ETL/ELT pipeline development.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Understanding of data lakes, data warehouses, and scalable data architectures.
• Experience with API-based integrations and large-scale data processing.
• Familiarity with tools such as Airflow, dbt, or Apache Spark is a plus.
• Strong problem-solving, collaboration, and analytical skills.

Qualifications:

• Exposure to AI/ML data preparation, RAG architectures, and vector databases.
• Experience supporting analytics or AI-driven enterprise platforms.
• Background in higher education or multi-tenant data environments is an advantage.