Data Engineer-reading, PA-Onsite

Sr Data Platform Engineer / Platform Lead 

Location: Reading, PA 
Employment Type: Full-Time 
 

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. 

• Responsibilities 

• 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 

Core Skill Set Required 

• 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 relational databases (e.g., PostgreSQL) 

• 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 

• Good 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) 

• Experience building or supporting SaaS products 

• Specialized experience with secure data sharing in Snowflake