Senior Data Engineer

ICON is seeking a Senior Software/Data Engineer I to join our Data Intelligence & Systems Architecture (DISA) team. This engineer will play a foundational role in shaping, developing, and scaling ICON’s enterprise data platform within Palantir Foundry, owning the ingestion, modeling, and activation of data that powers reporting, decision-making, and intelligent automation across the company. You will not just build pipelines. Instead, you will be architecting the Digital Twin of an industrial robotics and construction company. You will work closely with teams across Supply Chain & Manufacturing, Logistics, Engineering Support Services, Software, Field Operations and Technology R&D to centralize high-value data sources, model them into scalable assets, and enable business-critical use cases. Use cases will range from real-time reporting and analytics to AI/ML-driven operational workflows and decision-making. This is a highly cross-functional and technical role, ideal for someone with strong data engineering skills, deep business curiosity, and a bias toward action. This role is based at ICON’s headquarters in Austin, TX and reports to the Senior Director of Operations. Responsibilities Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines in Palantir Foundry (and supplemental tools) to integrate data from enterprise systems (NetSuite, Workday, etc [... source excerpt omitted ...] Modeling & Ontology: Develop and refine data models that organize enterprise data into meaningful structures. Leverage Foundry’s ontology features to define business objects (e.g. Customers, Work Orders, Inventory Items) and ensure data is linked in a way that reflects real-world relationships. Continuously improve these models for new business requirements – for instance, adding new attributes or new object types as we launch new programs. Data Quality & Governance: Implement data validation and quality checks in pipelines to ensure data accuracy and consistency. Monitor pipeline runs and set up alerts for anomalies or failures. Work with the team to enforce data governance pol [... source excerpt omitted ...] , maintainable pipeline code. Establish best practices for code versioning, documentation of data transformations, and general data engineering standards within the team. Minimum Qualifications 7+ years of experience in data engineering or ETL development, handling large-scale datasets and complex pipelines. Strong foundation in data integration concepts and database design. Advanced Python skills for data processing (Pandas, etc.) and scripting, as well as solid SQL skills for querying and transforming data. Experience with PySpark or similar distributed data frameworks is a plus (Foundry uses Spark under the hood for big data). Experience building pipelines with enterprise data f