Senior Data Engineer

Howard University is hiring a Senior Data Engineer to build and maintain production-ready data infrastructure for institutional analytics and decision-making.

Responsibilities

• Design, develop, test, and maintain scalable ETL/ELT pipelines integrating data from student information systems, admissions platforms, financial aid systems, ERP systems, APIs, databases, flat files, and other institutional sources.
• Develop and maintain enterprise data models, data structures, transformation logic, and standardized datasets for institutional reporting and advanced analytics.
• Build automated ingestion, transformation, validation, and delivery pipelines using Python, R, SQL, and PySpark for large, complex datasets.
• Design and support cloud-based data lakehouse architectures, organizing data across raw, curated, and analytics-ready layers.
• Establish and maintain data lineage, metadata, business rules, data dictionaries, and source-to-target mappings to strengthen data transparency and governance.
• Create automated data-quality controls to detect missing, inconsistent, duplicate, or anomalous records and support resolution with data owners and stewards.
• Optimize pipelines, SQL queries, storage structures, and distributed processing workloads for performance, scalability, reliability, and cost efficiency.
• Support institutional data governance standards for data ownership, access, security, documentation, retention, and quality.
• Develop reusable data assets and standardized datasets for dashboards, institutional research, enrollment forecasting, financial modeling, predictive analytics, and executive reporting.
• Collaborate with functional offices to translate business requirements and institutional definitions into reliable technical solutions.
• Implement monitoring, logging, error handling, testing, version control, and documentation to support production-grade data operations.
• Protect sensitive institutional information and support compliance with FERPA, institutional security policies, and applicable data privacy requirements.
• Provide technical guidance and mentorship to analysts, data engineers, and other team members on data engineering standards and best practices.

Requirements

• Advanced proficiency in SQL, Python, and/or R, with experience using PySpark or comparable distributed data-processing technologies.
• Strong knowledge of data modeling, data structures, relational databases, and ETL/ELT pipeline development.
• Familiarity with modern cloud data platforms, data lakes, data warehouses, and lakehouse architectures.
• Knowledge of data governance, data lineage, metadata management, data quality, and role-based data access.
• Experience integrating data across APIs, databases, enterprise systems, and structured and semi-structured data sources.
• Familiarity with version control, automated testing, CI/CD, and production deployment practices.
• Experience working with higher education data and enterprise systems, including student, enrollment, admissions, financial aid, finance, or HR data.
• Ability to develop reliable analytics-ready datasets supporting institutional reporting, forecasting, advanced analytics, and machine learning.
• Strong analytical and problem-solving skills, with the ability to independently manage complex data engineering projects.
• Excellent written and verbal communication skills, with the ability to collaborate with technical and non-technical stakeholders.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, Engineering, Quantitative Methods, or a related field, with at least five (5) years of relevant higher education data experience.
• Alternatively, Master’s degree in Data Science, Educational Psychology with a Statistics/Quantitative Methods concentration, Quantitative Measurement, Statistics, Computer Science, Information Systems, or a related quantitative field, with at least three (3) years of relevant higher education data experience.

Technologies

• Python
• R
• SQL
• PySpark
• CI/CD
• FERPA

Benefits

• Comprehensive medical, dental, and vision insurance, plus mental health support
• PTO, paid holidays, flexible work arrangements
• Competitive salary; 403(b) with company match
• Ongoing training, tuition reimbursement, and career advancement paths
• Wellness programs, commuter benefits, and a vibrant company culture

Job Details

• Location: Washington, DC (onsite)
• Compensation Range: USD 120,000 - 140,000 per year
• Experience: Minimum 5 years
• Reporting: To the Chief Data and Analytics Officer

Compliance

• Compensation Range Disclosure: $120,000 - $140,000