Peterbilt Motors Company
On highways, construction sites, city streets, logging roads – everywhere our customers earn their living – Peterbilt’s red oval is a familiar symbol of performance, reliability and pride. Peterbilt has reigned as America’s premium quality truck manufacturer since the company’s founding in 1939. Our dedication to deliver products and services focused on improving customers’ performance, image, profitability and peace of mind truly makes Peterbilt the Class of the Industry.
This position is for a Data Engineer with the Peterbilt Advanced Analytics team. This team focuses on solving Peterbilt’s most important challenges using Data and Advanced Analytics. The Advanced Analytics team works on a huge variety of projects; from predictive analytics models to support Operations, to prescriptive analytics to support Peterbilt sales efforts, and data mining projects to identify the drivers of warranty claims. This team works on high-impact and high-visibility projects. Data Engineers present their work to senior executives, helping shape not only Peterbilt’s current business, but its long term strategy.
The team embraces a collaborative approach to Data Science, sharing best practices and new ideas. Come join this dynamic, growing and pioneering team!
· Build and support automated data pipelines from a wide range of data sources using an AWS, Informatica, Attunity, and Snowflake based technology stack with an emphasis on automation and scale
· Contribute to overall architecture, framework, and design patterns to store and process high data volumes
· Develop solutions to measure, improve, and monitor data quality based on business requirements
· Ensure product and technical features are delivered to spec and on-time
· Design and implement reporting and analytics features in collaboration with product owners, analysts, and business partners within an Agile / Scrum methodology using tools like Tableau, SumoLogic, and ThingWorx
· Proactively support product health by building solutions that are automated, scalable, and sustainable – be relentlessly focused on minimizing defects and technical debt
· Provide post-implementation production support for data pipelines
· Partner with the business unit organizations to understand their data engineering and IoT needs, develop use cases, generate processes, and develop overall solution requirements.
· Masters’ degree in Computer Science or a related field required
· 3+ years of experience in a data engineering role
· 2+ years of experience with AWS and related services (e.g., EC2, S3, SNS, Lambda, IAM)
· Experienced with Informatica, Attunity, and Snowflake
· Experience with dimensional modeling, ETL (including SSIS), reporting tools, data warehousing (Redshift & Snowflake), structured and unstructured data, relational databases (SQL Server & PostgreSQL), graph databases (Neo4J), and NoSQL databases (MongoDB & DynamoDB)
· Significant experience with, or deep understanding of, programming (Python, SQL, Java, or C#).
· Experience with working with big data (Scala, Spark).
· Experience with participating in projects in a highly collaborative, multi-discipline team environment
· Must be a highly-motivated self-starter and self-directed learner with a creative mind, high attention to detail and a solution-oriented outlook
· Candidate must demonstrate strong analytical skills, excellent general business acumen, with the ability to concisely and clearly communicate complex topics.
· Experienced with SCADA software systems and industrial protocols (HTTP and MQTT)
· Experienced with Continuous Integration/Deployment using Jenkins, Terraform, CloudFormation and AWS CodePipeline
· Experienced with shell scripting
· Experience with container deployments (Docker, Kubernetes, ECS).
· Experience with the operationalization and maintenance of analytics APIs using Plumber, Flask, Swagger and similar
· Experience in leveraging platforms such as PTC ThingWorx, AWS IoT
· Requires frequent sitting and walking.
· Availability to work “on-call” 24 hours/day for emergencies, and flexibility in schedule and priority demands including supporting an enterprise level Data Center.
· Position could be required to minimal traveling up to 20%