Data Engineer - INTL - India

Job Description
This role will be responsible for designing, building, and optimizing data pipelines and architectures to support the integration, analytics, and modeling needs of our TMS platform.

The Data Engineer will work closely with cross-functional teams to ensure data integrity, scalability, and actionable insights, with approximately 20% of the role dedicated to data modeling for transportation and logistics analytics.

Experience with Google Cloud Platform (GCP) is required.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.

We are an equal opportunity/affirmative action employer that believes everyone matters.

Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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Skills and Requirements
-5+ years of hands-on experience architecting and building data pipelines and ETL processes, ideally within transportation, logistics, or supply chain environments.
-Proven track record (3+ years) designing and implementing complex data models for analytics and reporting, with direct experience supporting Transportation Management System (TMS) implementations.
-Extensive expertise (3+ years) working with Google Cloud Platform (GCP) services, including BigQuery, Dataflow, Cloud Storage, and related data engineering tools.
-Advanced proficiency in Python and SQL, with demonstrated ability to optimize queries and manage large-scale data processing in production environments.
-Strong history of cross-functional collaboration, partnering with business stakeholders, solution architects, and analytics teams to deliver scalable, reliable, and actionable data solutions.