Senior Data Engineer

Job Type Full-time Description

Senior Data Engineer

South College - We are one of the nation’s fastest growing institutions of higher learning … come grow your career with us. In order to fully meet our Mission to our students, we require a diverse combination of perspectives, backgrounds, life experiences, and ideas from our faculty and staff and will provide them with an equitable and inclusive work environment -where respect and open interchange of ideas are at the heart of that culture.

Over 16,000 Students

10 Campuses

Competency Based Education

Online

Senior Data Engineer Description

At South College, we are committed to providing a high-quality education that prepares students for success in their careers. As a Senior Data Engineer on our team, you’ll play a key role in helping us harness the power of data to improve student outcomes, optimize operations, and drive innovation. You’ll have the opportunity to work in a dynamic and collaborative environment while continuing to grow and advance in your career.

The person in this position will be responsible for building and managing robust data pipelines, designing scalable data architectures, and enabling advanced analytics capabilities to support various academic and administrative functions across the college. This role will collaborate closely with stakeholders to understand data requirements, implement solutions, and facilitate data-driven insights and initiatives.

If you’re passionate about data engineering and want to make an impact at a forward- thinking institution, we encourage you to apply!

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes to ingest data from diverse sources into centralized data repositories.
• Architect and implement data warehouses, data lakes, and analytical databases to support reporting, analytics, and business intelligence initiatives.
• Develop and maintain data models, schemas, and metadata definitions to ensure consistency, accuracy, and integrity of data assets.
• Collaborate with stakeholders to define data requirements, KPIs, and metrics, and translate them into actionable data solutions and visualizations.
• Implement data governance practices, data quality standards, and data security measures to ensure compliance and confidentiality of sensitive data.
• Integrate third-party data sources and APIs to enrich and enhance existing datasets and enable advanced analytics and predictive modeling.
• Optimize data infrastructure and processes for performance, scalability, and cost- effectiveness, leveraging cloud-based technologies and distributed computing frameworks.
• Develop and maintain data documentation, data dictionaries, and data lineage to facilitate understanding and utilization of data assets.
• Stay current with emerging technologies, industry trends, and best practices in data engineering, analytics, and machine learning.
• Ensure compliance with data privacy regulations (e.g., FERPA, GDPR) while handling student and institutional data.

Requirements

Education

• Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field. (Master’s degree preferred)

Experience

• 4-10 years’ experience as a Data Engineer, Data Architect, or similar role, with hands-on experience in designing and implementing data solutions.
• Proven experience in designing and implementing end-to-end data solutions.
• Hands-on experience with major cloud platforms such as:
  • Microsoft Azure
  • Amazon Web Services (AWS)
  • Google Cloud Platform (GCP)
• Proficiency with big data technologies and frameworks
• Familiarity with business intelligence and data visualization tools, such as:
  • Power BI
  • Tableau
• Experience with statistical computing tools and languages, particularly:
  • R
  • Python’s data stack (e.g., pandas, NumPy, SciPy, matplotlib, scikit-learn)

Skills

• Strong programming skills in:
  • Python
  • SQL
  • R
  • C#
• Deep understanding of:
  • Data manipulation, cleansing, transformation, and analysis
  • ETL pipelines and data integration workflows
  • Relational databases (e.g., MS SQL Server, MySQL)
  • NoSQL databases (e.g., MongoDB, Cassandra)
• Knowledge of data modeling techniques, database architecture, and performance optimization.
• Demonstrated ability to:
  • Lead data engineering projects
  • Mentor junior engineers
  • Collaborate with cross-functional teams including analytics, product, and business stakeholders.
• Excellent problem-solving skills, attention to detail, and ability to manage and prioritize multiple complex projects.
• Strong communication and interpersonal abilities for both technical and non-technical audiences.