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L3Harris Technologies

Global defense contractor delivering aerospace tech

Senior Associate - Application Developer, Data Engineer

Data EngineeringUpdated on Nov 14
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree and at least two years of prior relevant experience, or a graduate degree or equivalent with zero to two years of prior related experience; in lieu of a degree, at least six years of prior related experience.
  • Familiarity with modern programming languages such as Python, TypeScript, JavaScript, or similar is preferred.
  • Experience building, supporting, or maintaining data pipelines, ETL/ELT workflows, or system integrations is preferred.
  • Experience with relational or non-relational databases, structured and semi-structured data, and transformation logic is preferred.
  • Understanding of version control, code reviews, unit testing, debugging, and continuous integration/continuous delivery concepts is preferred.
  • Familiarity with data quality, validation, and troubleshooting techniques in data workflows is preferred.
  • Experience with Palantir Foundry, including Pipelines, Code Repositories, Ontology, Workshop, Operational Applications, or ontology-based development is preferred.
  • Experience designing or supporting robust, high-performance enterprise data pipelines across multiple source systems is preferred.
  • Experience implementing business logic within data transformations for operational or analytical use cases is preferred.
  • Exposure to artificial intelligence or machine-learning-enabled workflows, analytics applications, or operational data products is preferred.
  • Experience in regulated industries such as defense, aerospace, manufacturing, finance, or healthcare is preferred.
  • Familiarity with secure software development practices, data governance concepts, and enterprise data management principles is preferred.

Responsibilities

  • Build and optimize robust, reliable, high-performance pipelines supporting 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.
  • Troubleshoot pipelines, tune performance, and resolve defects to improve resilience, maintainability, and scalability.
  • Translate business requirements, operational processes, and domain rules into data transformation logic that produces meaningful, trusted, consumable data assets.
  • Implement transformation frameworks that consistently encode business logic 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 curated datasets and reusable data products supporting analytics, reporting, operational workflows, and AI-enabled applications.
  • Work with data architects and senior engineers to align pipelines and data products with enterprise architecture standards and standardized ontology models within Palantir Foundry.
  • Support implementation and refinement of ontology-aligned datasets, object relationships, and semantic models that enable interoperability across domains and applications.
  • Contribute to common patterns, naming conventions, governance practices, and integration standards that improve consistency and reuse across the platform.
  • Partner with architecture teams to ensure data engineering solutions are scalable, maintainable, and aligned with 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, reliable deployment of data solutions in a regulated environment.
  • Write clean, maintainable, 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.
  • Use 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 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.

Desired Qualifications

  • 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.

About the Company

L3Harris Technologies

Global defense contractor delivering aerospace tech

L3Harris Technologies provides advanced aerospace, defense, and space systems for governments and commercial customers. Its products include sensors, communications, and propulsion—such as tactical radios, night-vision gear, satellite payloads, missile defense, and space propulsion—delivered as integrated systems for operations across air, land, sea, space, and cyber domains. The company blends legacy technologies from two joining giants with newer capabilities, faster acquisition cycles, and a focus on missiles, space, and resilient communications to field solutions quickly. Its goal is to be a trusted, scale-ready provider of next‑generation defense and intelligence capabilities for national security and related customers.

Company size
10,001+
Company stage
IPO
Headquarters
Melbourne, FL
Founded
1895

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