Data Engineer

RFA Engineering•Urbandale, IA

62d•Onsite

About The Position

RFA Engineering supports industry-leading clients through the full software development lifecycle to build cutting-edge precision agriculture, machine guidance, vehicle automation and autonomy applications. We are seeking passionate, talented engineers to work on exciting projects using the latest tools and technologies including robotics, computer-vision, machine learning, IoT, cloud computing, and much more. Collaborate with a team of industry experts onsite at our client's world-class engineering center and contribute to developing innovative solutions that drive sustainable agriculture practices. This is a full-time position with a full benefit package listed below that includes opportunities for professional growth, direct hire by our customers, and additional opportunities within our own organization. As a Data Engineer, you will enable engineers, analysts, and data scientists to more effectively access, explore, and leverage enterprise data to generate insights, build models, and make data-driven decisions. This role focuses on designing scalable cloud-based data solutions, developing high-quality datasets, and creating data products that empower individual contributors to work independently with complex, high-volume data. A key component of this role involves collaborating with embedded and digital engineering teams to define, capture, and analyze system performance, UI, and health metrics. You will help translate raw signals into actionable insights through analytics, dashboards, and monitoring tools.

Requirements

Bachelor’s degree or higher in Computer Science, Software Engineering, Data Engineering, or a related technical field, or equivalent professional experience
Demonstrated experience designing and implementing cloud-based data solutions in production environments
Strong proficiency in Python for data engineering and analytics applications
Experience working with data access and processing technologies such as SQL, PySpark, Databricks, Postgres, and MongoDB
Experience building and maintaining datasets at scale across multiple data formats and structures
Familiarity with vehicle or embedded system data, including CAN signals
Excellent written and verbal communication skills, including the ability to lead meetings, clearly document work, communicate proof-of-concepts, and collaborate across teams

Nice To Haves

Experience developing dashboards and visual analytics solutions using tools such as Tableau, Plotly, or similar platforms
Familiarity with spatial data and visualization tools such as Folium or Plotly
Experience implementing system monitoring, alerting, and health-tracking solutions
Strong analytical and problem-solving skills with the ability to debug complex data and system issues
Ability to work effectively in a self-directed environment with minimal oversight
Proven ability to manage multiple schedules, deliverables, and stakeholders simultaneously
Knowledge of off-highway, agricultural, construction, or industrial equipment data systems is a plus

Responsibilities

Design, build, and maintain cloud-based data pipelines and data products that support analytics, machine learning, and exploratory data analysis
Enable self-service data access by developing well-structured, documented, and discoverable datasets for individual contributors
Partner with embedded and digital engineering teams to define required performance, UI, and system health metrics and ensure appropriate data capture
Perform analytics and data aggregation to translate raw signals into meaningful insights and visualizations
Develop and maintain production-ready Python code and data workflows using SQL, PySpark, Databricks, and related technologies
Manage and optimize storage of diverse data types, including images, raster data, parquet files, time-series data, geo-tagged data, text, and other unstructured data
Build dashboards and interactive data applications using tools such as Tableau, Plotly Dash, or similar web-based visualization frameworks
Develop alerting and monitoring solutions (e.g., automated email notifications) to identify system performance issues or data pipeline failures
Collaborate in code reviews, documentation, and best-practice development to ensure maintainable and reproducible solutions
Manage multiple projects, priorities, and milestones while maintaining a strong sense of ownership and accountability