Senior Data Engineer

Howard University; Washington (District of Columbia); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and vis

PTO, holidays, flexible work

403(b) with company match

Tuition reimbursement and training

Vibrant university culture

Job summary

Howard University seeks a Senior Data Engineer to build and maintain production-ready data infrastructure for institutional analytics and decision-making. You will design ETL pipelines from student systems, admissions, financial aid, ERP, APIs, databases, and flat files to support reporting and analytics.

You will implement cloud-based data lakehouse architectures, data lineage, metadata, data quality, and governance, mentoring analysts and engineers while ensuring FERPA compliance and scalable,

Qualifications

• Advanced proficiency in SQL, Python and/or R with PySpark experience.
• Strong data modeling, relational databases, and ETL/ELT pipeline development.
• Familiarity with cloud data platforms, data lakes, and lakehouse architectures.
• Knowledge of data governance, lineage, metadata, quality, and access control.
• Experience integrating data from APIs, databases, and enterprise systems.
• Familiarity with version control, automated testing, CI/CD, and production deployment.
• Experience with higher education data domains (student, enrollment, finance, HR).
• Ability to deliver analytics-ready datasets for reporting, forecasting, analytics, ML.
• Excellent communication and collaboration with technical and non-technical stakeholders.
• Bachelor’s or Master’s degree with 3–5+ years higher education data experience.

Responsibilities

• Design, develop, test, and maintain scalable ETL/ELT pipelines across multiple institutional sources.
• Develop and maintain enterprise data models, datasets, and transformation logic for reporting.
• Build automated ingestion and delivery pipelines using Python, R, SQL, and PySpark for large datasets.
• Design and support cloud-based data lakehouse architectures and data governance practices.
• Establish data lineage, metadata, dictionaries, and source-to-target mappings.
• Create automated data-quality controls and collaborate with data owners for resolution.
• Optimize pipelines, queries, storage, and distributed processing for performance and cost.
• Support data governance standards including data ownership, access, security, and retention.
• Develop reusable data assets for dashboards, institutional research, forecasting, and analytics.
• Collaborate with offices to translate business requirements into reliable technical solutions.
• Implement monitoring, logging, testing, version control, and documentation for production-grade ops.
• Ensure compliance with FERPA and institutional security policies and privacy requirements.
• Provide technical guidance and mentorship to analysts and engineers on standards and best practices.

Skills

SQL

Python

R

PySpark

CI/CD

FERPA

Education

Bachelor’s degree in a quantitative field

Master’s degree in a quantitative field

Tools

CI/CD tooling

FERPA compliance

Job description

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