Data Engineer

Oshkosh Corporation • Frederick, MD

2d • $82,900 - $134,300

About The Position

As a member of the Advanced Data Analytics team, the Data Engineer works with a cross-functional team to develop and execute the data analytics strategy and apply it to Oshkosh Corporation products. The work encompasses acquiring, processing, and applying machine learning to engineering or service data for preventive maintenance and intelligent control of on- or off-road vehicles.

The role designs scalable ETL solutions to deliver structured and unstructured data from source systems to analytics platforms, including batch and streaming data. It supports enterprise-wide analytics through data testing, validation, governance, performance tuning, troubleshooting, rapid prototyping, architectural documentation, and collaboration across disciplines and business segments.

Requirements

• Bachelor’s degree in computer science, data science, or a related field.
• Three or more years of experience working as a data engineer, ETL developer, and/or data warehouse DBA.

Nice To Haves

• Experience with big data tools and architectures such as Cloudera Hadoop, HDFS, Hive, and Spark.
• Working knowledge of telematics interfaces and streaming solutions such as MQTT, NiFi, and Kafka.
• Automotive or heavy-duty on- or off-road vehicle experience, including digital data bus, Ethernet, or Controller Area Network (CAN) experience.
• Highly organized and detail-oriented, with strong critical-thinking, analytical, and problem-solving skills.
• Ability to manage multiple tasks in a fast-paced environment, independently and as part of a team.
• Excellent interpersonal skills and ability to present information effectively and respond to questions from leadership and peers.
• Strong proficiency with SQL, Bash, and Python, and experience with the Anaconda distribution.

Responsibilities

• Design and develop scalable ETL solutions to deliver structured and unstructured batch and streaming data from source systems to analytics platforms.
• Test and validate data transformations and verify data used for enterprise-wide analytics.
• Assist with data governance, including data quality and security, within data lakes and enterprise data warehouses across business segments.
• Assist with performance-tuning data processes and troubleshoot data-processing issues.
• Collaborate, coordinate, and communicate across disciplines, departments, and business segments.
• Develop rapid-prototyping and design processes to deliver solutions to the business quickly.
• Maintain reference architecture and documentation for architectural governance and application roadmaps.
• Help educate others on data best practices, including data modeling, database design, ETL design, job scheduling, and monitoring.
• Assist with or direct feasibility studies and project estimates, including manpower, budget development, and timelines, for proposed research and development projects.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level