Senior Data Engineer – Data Architecture for Data Science & Machine Learning

Job Description

Company: Penn State University
Location: Reston, VA (or State College, PA)
Workplace Type: On-site
Employment Type: Full-time
Pay / Compensation: $146,040.00 – $318,840.00

About the Role

Penn State University’s Applied Research Laboratory (ARL) is seeking a Senior Data Engineer with deep expertise in database design, optimization, and data access strategies to support our growing data science and machine learning initiatives within the Information Science Division. In this role, you will architect and optimize data systems that empower our data scientists to efficiently research, train, and deploy both traditional and ML-based algorithms and applications.

What You’ll Do / Key Responsibilities

• Design and Maintain Database Solutions: Build and maintain scalable, high-performance database solutions to support data science workflows and ML experimentation.
• Collaborate on Access Patterns: Partner with data scientists to understand data access patterns and develop storage strategies that accelerate analysis and model training.
• Serve as PostgreSQL Subject Matter Expert: Lead initiatives around PostgreSQL schema design, indexing, partitioning, and query optimization.
• Evaluate Alternative Technologies: Evaluate and integrate alternative database technologies (e.g., MongoDB, Neo4j, Redis, Cassandra) where they provide clear advantages.
• Optimize Data Pipelines: Lead efforts to optimize data pipelines for both structured and unstructured data used in algorithm development.
• Ensure Data Governance: Ensure data integrity, security, and governance across storage systems.
• Implement Monitoring and Automation: Implement monitoring, automation, and performance-tuning tools for all database environments.

Requirements & Qualifications

• 5+ years of experience in data engineering, database architecture, or related technical roles.
• Expert-level proficiency in PostgreSQL (query tuning, schema design, indexing, partitioning, replication).
• Strong understanding of data modeling, normalization vs. denormalization tradeoffs, and query optimization.
• Experience with non-relational databases (e.g., MongoDB, Cassandra, Neo4j, Redis, or DynamoDB).
• Familiarity with machine learning workflows and how data is consumed for training, evaluation, and deployment.
• Experience with cloud database services (AWS RDS/Aurora, GCP Cloud SQL, Azure Database).
• Proficiency in SQL and one or more scripting languages (Python preferred).
• Excellent communication and collaboration skills—comfortable working closely with data scientists, ML engineers, and software developers.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• U.S. citizenship required and must be eligible to obtain a government security clearance.

Preferred / Bonus Qualifications (if applicable)

• Experience architecting hybrid data ecosystems spanning relational, NoSQL, and analytical databases.
• Knowledge of data lake, warehouse, and feature store architectures (e.g., Snowflake, Redshift, BigQuery, Feast).
• Familiarity with ETL/ELT frameworks and data orchestration tools (e.g., Airflow, dbt).

Benefits & Perks (if applicable)

• Comprehensive medical, dental, and vision coverage.
• Robust retirement plans and substantial paid time off (holidays, vacation, and sick time).
• Generous 75% tuition discount available to employees as well as eligible spouses and children.

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.