Data Engineer – Data Architecture for Data Science & Machine Learning

POSITION SPECIFICS

We are 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 of the Applied Research Laboratory (ARL) at Penn State. 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.

The ideal candidate is a PostgreSQL expert who also brings hands‑on experience with other modern data storage technologies—such as No

SQL, graph, and time‑series databases
—and can guide the organization in choosing the right tools and structures for each data use case.

ARL is an authorized DoD Skill Bridge partner and welcomes all transitioning military members to apply.

• Design and maintain scalable, high‑performance database solutions to support data science workflows and ML experimentation
• Partner with data scientists to understand data access patterns and develop storage strategies that accelerate analysis and model training
• Serve as the internal subject matter expert on PostgreSQL
  —including schema design, indexing, partitioning, and query optimization
• Evaluate and integrate alternative database technologies (e.g., MongoDB, Neo4j, Redis, Cassandra) where they provide clear advantages
• Lead efforts to optimize data pipelines for both structured and unstructured data used in algorithm development
• Ensure data integrity, security, and governance across storage systems
• Implement monitoring, automation, and performance‑tuning tools for all database environments
• Advise on data lifecycle management—balancing accessibility for R&D with efficiency and compliance requirements

• 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

• Experience architecting hybrid data ecosystems spanning relational, No
  
  SQL, and analytical databases.
• Knowledge of data lake, warehouse, and feature store architectures (e.g., Snowflake, Redshift, Big Query, Feast)
• Familiarity with ETL/ELT frameworks and data orchestration tools (e.g., Airflow, dbt)
• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field

Work location can be fully on‑site located in State College, PA or Reston , VA. Questions related to flexible work should be directed to the hiring manager during the interview process.

If filled as R&D Engineer
- Data Science (ARL) - Principal Professional, this position requires:
Bachelor's Degree
- Engineering or Science
19+ years of relevant experience

Required

Certifications:

None If filled as R&D Engineer
- Data Science (ARL) - Advanced Professional, this position requires:
Bachelor's Degree
- Engineering or Science5+ years of relevant experience

Required

Certifications:

None If filled as R&D Engineer
- Data Science (ARL) - Senior Professional, this position requires:
Bachelor's Degree
- Engineering or Science
14+ years of relevant experience

Required

Certifications:

None

ARL's purpose is to research and develop innovative solutions to challenging scientific, engineering, and technology problems in support of the Navy, the Intel Community (IC), and other federal government customers.