Principal Data Scientist/Engineer

Position Overview

At Parsons, imagine a career where you thrive, work with exceptional people and are empowered to redefine what's possible. We are seeking an amazingly talented Principal Data Scientist/Engineer responsible for designing, developing, and maintaining robust and scalable data pipelines for enterprise AI applications. Working within our innovative Federal Solutions team, you will collaborate with AI/ML engineers and data scientists to optimize data access and ensure the quality, integrity, and security of our data infrastructure.

Key Responsibilities

• Design, develop, and maintain robust and scalable data pipelines for enterprise AI applications, including defining appropriate data model concepts.
• Develop high-performance data parsers for extremely large and complex datasets.
• Implement and manage various database systems, including graph, SQL, NoSQL, and vector databases.
• Collaborate with AI/ML engineers and data scientists to understand data requirements and optimize data access and retrieval for AI models.
• Ensure data quality, integrity, and security across all data storage solutions.
• Support the deployment and maintenance of AI applications by providing expert data engineering capabilities.
• Familiarity with AI concepts in the context of data storage, access, and retrieval.
• Continuously optimize data infrastructure for performance, cost-efficiency, and scalability.

Required Qualifications

• Active TS/SCI w/Polygraph required for consideration.
• Bachelor’s degree in a relevant technical field with 10 years of experience; or Master’s degree with 8 years of experience (additional experience may be considered in lieu of a degree).
• Advanced proficiency in programming languages commonly used for data engineering (e.g., Python, Java, Scala).
• Demonstrated expertise in designing, developing, and optimizing data pipelines for large-scale enterprise environments.
• Proven experience with corporate dataflows and developing data parsers for extremely large datasets.

Preferred Qualifications

• Extensive experience with various database technologies including graph databases (e.g., Neo4j), SQL databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and vector databases.
• Familiarity with cloud platforms (AWS, Microsoft Azure) for data storage and processing.
• Excellent communication and interpersonal skills for collaborating with cross-functional teams.
• Ability to translate complex data requirements into actionable engineering solutions.
• Experience with data governance, data security, and compliance best practices.
• Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
• Experience with data warehousing concepts and tools.
• A continuous learning mindset to stay current with cutting-edge data engineering and AI advancements.
• Understanding of machine learning concepts and their implications for data infrastructure.

Benefits & Perks

• Compensation: $128,700.00 - $231,700.00
• Medical, Dental, and Vision coverage
• Paid Time Off
• 401(k)
• Life Insurance
• Flexible Work Schedules
• Holidays