Join our dynamic team as a Data Engineer, contributing to innovative data pipelines, analytical datasets, and enterprise reporting models. Your work will be pivotal in powering analytics, AI initiatives, manufacturing operations, and connected vehicle platforms, directly influencing executive decision-making. You'll collaborate closely with Analytics and AI teams to deliver robust data products that enhance Tableau dashboards and business intelligence solutions.

Develop and maintain robust ETL/ELT pipelines utilizing Spark, Airflow, Kafka, MQTT, and cloud-native technologies. Construct and optimize Redshift data models, analytical datasets, and reporting structures. Create and maintain Tableau-consumable datasets and certified reporting layers. Integrate diverse data sources including manufacturing, charging, IoT, ERP, CRM, and operational data. Support comprehensive data quality, validation, reconciliation, and monitoring processes. Design and implement business-focused dimensional models and analytical data marts. Partner with Analytics Engineers and business stakeholders to elevate reporting accuracy and performance. Aid in Tableau data source development and reporting initiatives. Enhance Redshift query performance and data processing efficiency. Actively participate in GitLab-based development, testing, deployment, and code review cycles.

A Bachelor's degree in Computer Science, Engineering, Analytics, or a related field is required, alongside 3-7 years of dedicated Data Engineering experience. Proficiency in SQL and Python programming is essential, along with hands-on experience with Redshift, Spark, Airflow, Kafka, MQTT, and cloud-based data architectures. Experience supporting Tableau reporting environments and business intelligence solutions is crucial. A solid understanding of dimensional modeling, data warehousing, and enterprise reporting architectures is necessary. Prior experience in Manufacturing, Automotive, EV, or IoT sectors is highly preferred.