Senior Associate, Data Architect

Job Description:

The Data Architect role is an early career position that supports the development of data solutions in a project-based environment. Working with senior data architects, business intelligence analysts, and cross-functional teams, this individual will help with data modeling, data integration, migration activities, and reporting solutions while learning L3Harris tools, standards, and best practices. This role is a good fit for candidates with interest or experience in either back-end data architecture work or front-end analytics and reporting, with the opportunity to grow across both areas over time.

Essential Functions:

• Support senior data architects in the design and maintenance of data models and data solutions.


• Assist with data integration, extract, transform, and load (ETL), and data migration activities across multiple sources.


• Help develop and maintain logical and physical data models based on business and technical needs.


• Support enterprise data environments, including data warehouses and platforms such as Snowflake and Palantir.


• Assist with dashboards, reports, and analytic outputs using tools such as Power BI, Tableau, or similar platforms.


• Troubleshoot data processing, reporting, and data quality issues.


• Collaborate with project teams and stakeholders to support solution development and delivery.


• Participate in testing, deployment, maintenance, and documentation of data solutions.


• Travel up to 10% as required.

Qualifications:

• To be eligible, applicants must be pursuing a master's degree in Systems Engineering, Electrical Engineering, Computer Science, Physics, Mathematics, Engineering or related field or have completed their master's degree within the last 12 months, regardless of age.

Preferred Additional Skills:

• Exposure to Palantir or similar enterprise data platforms.


• Familiarity with data warehouses such as Snowflake.


• Familiarity with Power BI, Tableau, Power Query, Power Pivot, or similar analytics tools.


• Exposure to relational or non-relational databases.


• Interest in learning enterprise data architecture standards and best practices.


• Curiosity, willingness to try new approaches, and openness to learning and using new technologies to grow technical skills. Basic knowledge of SQL, Python, or similar scripting or query languages.


• Foundational understanding of data modeling, data structures, analytics, reporting, or data management concepts.


• Exposure to either back-end data work such as ETL, integration, migration, or modeling, or front-end analytics work such as dashboards, reporting, and analysis.