Penske Logistics
From Penske Logistics's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
You’ll work alongside great people and on really cool projects.
Most people know Penske for our big yellow trucks. But we’re so much more than that. At Penske we have a 50-plus year history of leading the transportation and supply-chain industry, delivering world-class and award-winning technology solutions.
What most people don’t know, we are just as much a data company as we are a transportation and supply chain company. We collect and analyze billions of datapoints each year, through over 300+ advanced analytical models and integrate insights from our fleet, maintenance operations, and logistics networks to give customers a more complete view of their supply chains. That connected intelligence allows us to anticipate issues, optimize resources, and deliver reliable outcomes across transportation and logistics for our customers. Penske continues to invest in, and grow, our digital products – and we need talent at all levels to help us advance and continue to lead our industry.
While data is very important, the key to our success is our people. You’ll work alongside great people and on really cool projects. Ultimately, you’ll help develop and ensure our technology solutions keep our company and our customers moving forward.
This position is based out of our corporate offices in Reading. PA. This an office first position, at least 4 days in office.
Position Summary
As a Data Platform Engineer/Platform Lead within Digital Products, you'll help build and run the data platform behind our fleet and telematics products — from ingesting raw data through to the datasets and views that power our customer-facing applications. You'll work closely with Data Science and product teams, balancing hands-on pipeline development with platform-level decisions on cost, reliability, and scale.
Design, build, and maintain data pipelines and orchestration workflows that move data from ingestion through transformation to serving layers
Write and optimize SQL and PySpark for large-scale data processing and transformation
Tune cloud data warehouse performance and cost (query optimization, refresh/scheduling strategy, resource sizing) as data volume and usage scale
Build and maintain data quality checks and pipeline monitoring/alerting to catch issues before they reach downstream consumers
Partner with Data Science to support feature engineering and analytics pipelines feeding ML/analytics workloads
Collaborate with product and engineering stakeholders to translate business needs into reliable, scalable pipeline design
Support incident response, root-cause analysis, and continuous improvement of the data platform
Document architecture and pipeline design to support onboarding of new team members
Contribute to platform-level decisions on architecture, tooling, and technical direction as the team and data volume scale
Strong SQL skills, including query optimization
Proficient in Python and PySpark for large-scale/distributed data processing
Hands-on experience with a workflow orchestration tool (e.g., Apache Airflow)
Experience with a cloud data warehouse (e.g., Snowflake)
Experience with cloud data infrastructure (AWS), including cloud storage and distributed processing (e.g., S3, EMR/Spark)
8+ years in data engineering with hands-on ownership of production data pipelines
Strong communication skills; able to explain technical tradeoffs to both technical and non-technical stakeholders
Nice to Have
Familiarity with streaming or change-data-capture (CDC) ingestion patterns (e.g., Apache Kafka)
Experience building data quality frameworks and pipeline observability/alerting
Exposure to ML/analytics pipeline support (feature engineering, model-serving data prep)
Familiarity with monitoring and logging tools, such as Dynatrace, Prometheus, Grafana, or the ELK stack
Strong knowledge of DevOps principles, continuous integration, continuous delivery, and infrastructure automation
Hands-on experience with containerization technologies like Docker and container orchestration platforms like Kubernetes or OpenShift
Experience with CI/CD and collaboration tooling such as Bamboo, Bitbucket, and Confluence
Relevant certifications (e.g., SnowPro Core, SnowPro Advanced: Data Engineer, AWS Data Analytics)
Specialized experience with secure data sharing in Snowflake
The physical and mental demands described here are representative of those that must be met by an associate to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The associate will be required to: read; communicate verbally and/or in written form; remember and analyze certain information; and remember and understand certain instructions or guidelines. While performing the duties of this job, the associate may be required to stand, walk, and sit. The associate is frequently required to use hands to touch, handle, and feel, and to reach with hands and arms. The associate must be able to occasionally lift and/or move up to 25lbs/12kg. Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception and the ability to adjust focus.
Penske is an Equal Opportunity Employer.
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