Senior Associate, Application Developer - Data Engineer

L3Harris Technologies•Melbourne, VA

1d•$70,500 - $149,500•Remote

About The Position

L3Harris is undertaking one of the largest-scale Data/AI implementations in the defense contracting sector. This multi-year, transformative program is building state-of-the-art AI applications on top of unified data. It is integrating ~100 legacy systems—including enterprise resource planning (ERP), product lifecycle management (PLM), supply chain, finance, operations, and specialized domain systems. The capabilities cover dozens of critical corporate use cases spanning program management, finance, operations, supply chain, engineering, and strategic planning. The L3Harris Transformation team is seeking a Full Stack Developer to contribute to the development, testing, and support of applications, workflows, and data pipelines within the Palantir Foundry platform. This role will work as part of an agile, cross-functional team alongside architects, business system analysts, product owners, and senior developers to implement secure, scalable, and maintainable solutions that support critical enterprise use cases.

Requirements

Bachelor’s Degree and minimum 2 years of prior relevant experience.
Graduate Degree or equivalent with 0 to 2 years of prior related experience.
In lieu of a degree, minimum of 6 years of prior related experience.

Nice To Haves

Experience developing data-intensive software solutions using modern programming languages such as Python, TypeScript, JavaScript, or similar
Experience building, supporting, or maintaining data pipelines, ETL/ELT workflows, or system integrations
Experience working with relational or non-relational databases, structured and semi-structured data, and transformation logic
Understanding of software engineering best practices including version control, code reviews, unit testing, debugging, and CI/CD concepts
Familiarity with data quality, validation, and troubleshooting techniques in data workflows
Experience with Palantir Foundry, including Pipelines, Code Repositories, Ontology, Workshop, Operational Applications, or ontology-based development
Experience designing or supporting robust, high-performance enterprise data pipelines across multiple source systems
Experience implementing business logic within data transformations to support operational or analytical use cases
Exposure to AI/ML-enabled workflows, analytics applications, or operational data products
Experience in regulated industries such as defense, aerospace, manufacturing, finance, or healthcare
Familiarity with secure software development practices, data governance concepts, and enterprise data management principles

Responsibilities

Build and optimize robust, reliable, and high-performance pipelines that support enterprise-scale processing, data availability, and downstream application performance.
Implement data ingestion, transformation, enrichment, validation, and monitoring logic to ensure data products are accurate, timely, and operationally dependable.
Support pipeline troubleshooting, performance tuning, and defect resolution to improve resiliency, maintainability, and scalability.
Translate business requirements, operational processes, and domain rules into data transformation logic that produces meaningful, trusted, and consumable data assets.
Implement transformation frameworks that encode business logic consistently across source systems and downstream use cases.
Work with business analysts, product owners, and domain stakeholders to ensure data outputs reflect agreed-upon rules, calculations, and definitions.
Contribute to the development of curated datasets and reusable data products that support analytics, reporting, operational workflows, and AI-enabled applications.
Work closely with data architects and senior engineers to align pipelines and data products with enterprise architecture standards and standardized ontology models within Palantir Foundry.
Support the implementation and refinement of ontology-aligned datasets, object relationships, and semantic models that enable interoperability across domains and applications.
Contribute to the adoption of common patterns, naming conventions, governance practices, and integration standards to improve consistency and reuse across the platform.
Partner with architecture teams to ensure data engineering solutions are scalable, maintainable, and aligned to long-term enterprise data strategy.
Implement data quality checks, reconciliation logic, validation rules, and observability mechanisms to ensure confidence in enterprise data products.
Support governance requirements through traceable transformation logic, documentation, lineage awareness, and adherence to platform and enterprise standards.
Collaborate with security, infrastructure, and operations teams to support compliant, secure, and reliable deployment of data solutions in a regulated environment.
Write clean, maintainable, and well-documented code following team standards for version control, peer review, testing, and deployment.
Participate in unit testing, integration testing, debugging, and continuous improvement across pipeline and data product components.
Leverage modern engineering tools, including AI-assisted development tools where appropriate, to improve productivity, quality, and consistency.
Participate in agile ceremonies such as sprint planning, backlog refinement, daily standups, demos, and retrospectives.
Provide task status updates, identify blockers, and support delivery commitments for assigned work.
Work closely with architects, product owners, business analysts, and peer engineers to understand requirements and deliver effective technical solutions.
Contribute to continuous improvement of team engineering practices, tooling, and delivery processes.
Develop proficiency in Palantir Foundry development frameworks, enterprise data integration patterns, ontology-driven development, and data platform best practices.
Continuously build technical knowledge in data engineering, data modeling, software engineering, and enterprise platform delivery.