Senior Data Platform Engineer - Cloud & AI Modernization

Fa Etbx Saasfaprod1; Town of Vienna (WI); On-site; USD 140,000 - 190,000; Full time

Job summary

Navy Federal Credit Union seeks a Principal Data Engineer to provide senior engineering expertise and architectural direction across enterprise Data and Analytics Modernization initiatives in Vienna, VA. This role focuses on modernizing legacy data ecosystems, enabling trusted data products, and accelerating AI capabilities through scalable cloud-native architectures.

Responsibilities include designing scalable pipelines with Spark, Python, SQL, Databricks, Azure Data Factory, and Microsoft

Qualifications

• Bachelor’s degree or equivalent experience in information systems or a related field.
• Strong hands-on experience with Spark, Python, SQL, and Databricks.
• Experience building scalable cloud data pipelines and lakehouse architectures.
• Knowledge of data governance, metadata management, and data quality practices.

Responsibilities

• Lead design and implementation of scalable batch and real-time data pipelines.
• Modernize legacy analytical stores and BI workloads for cloud-native platforms.
• Drive data onboarding patterns using API management and streaming technologies.
• Mentor engineers and align delivery with enterprise standards and security.

Skills

Spark

Python

SQL

Databricks

Azure Data Factory

Power BI

Tableau

Microsoft Fabric

Education

Bachelor’s degree in information systems

Bachelor’s degree in Computer Science

Master’s degree in related IT discipline

Tools

Unity Catalog

Alation

Gravitee

Kafka

MuleSoft

Job description

Navy Federal Credit Union seeks a Principal Data Engineer to provide senior engineering expertise and architectural direction across enterprise Data and Analytics Modernization initiatives in Vienna, VA. This role focuses on modernizing legacy data ecosystems, enabling trusted data products, and accelerating AI capabilities through scalable cloud-native architectures.

Responsibilities include designing scalable pipelines with Spark, Python, SQL, Databricks, Azure Data Factory, and Microsoft