Join our dynamic team as a Data Engineer, instrumental in building and optimizing data pipelines and analytical models. This role is crucial for powering advanced analytics, AI initiatives, manufacturing operations, and critical business decision-making. You will collaborate closely with Analytics and AI teams to deliver robust data products that enhance Tableau dashboards and business intelligence solutions.

This position offers a unique opportunity to work with diverse data streams, including manufacturing, connected vehicles, and enterprise systems, contributing directly to the company's strategic goals.

Develop and maintain robust ETL/ELT pipelines leveraging technologies like Spark, Airflow, Kafka, and MQTT, alongside cloud-native solutions.

Construct and refine Redshift data models, analytical datasets, and reporting structures for optimal performance.

Create and manage Tableau-ready datasets and certified reporting layers.

Integrate data from various sources such as manufacturing, charging, IoT, ERP, CRM, and operational systems.

Oversee data quality, validation, reconciliation, and monitoring processes to ensure data integrity.

Design and implement business-focused dimensional models and analytical data marts.

Collaborate with Analytics Engineers and business stakeholders to enhance reporting accuracy and speed.

Support Tableau data source development and ongoing reporting efforts.

Optimize Redshift query performance and data processing workflows.

Actively participate in GitLab-based development, testing, deployment, and code review cycles.

Possess a Bachelor's degree in Computer Science, Engineering, Analytics, or a related technical discipline.

Bring 3 to 7 years of dedicated experience in Data Engineering.

Demonstrate strong proficiency in SQL and Python programming.

Showcase hands-on experience with Redshift, Spark, Airflow, Kafka, MQTT, and cloud-based data architectures.

Have proven experience supporting Tableau reporting environments and business intelligence platforms.

Exhibit a solid understanding of dimensional modeling, data warehousing principles, and enterprise reporting architectures.

Preference will be given to candidates with experience in Manufacturing, Automotive, EV, or IoT sectors.