[Hiring] Data Engineer @OnTrac

Role Description

We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and analytics solutions on Google Cloud Platform (GCP). This role will integrate data from on-premises systems, cloud-hosted servers, and SaaS applications through APIs and SFTP file transfers, creating reliable datasets that support reporting, business insights, and ML / AI.

Qualifications

• At least 5 years of relevant, hands-on experience building and supporting production data pipelines on GCP.
• Demonstrated strong SQL and Python skills for data extraction, transformation, integration, and automation.
• Hands-on experience with BigQuery and Cloud Storage along with relevant GCP orchestration and data processing services.
• Experience integrating data from on-premises databases, cloud-hosted systems, REST APIs, and SFTP file transfers.
• Understanding of data modeling, ETL/ELT patterns, incremental loading, and data quality practices.
• Familiarity with access controls, service accounts, secrets management, and secure connectivity across on-premises and cloud environments.
• Experience with version control, automated deployments, and production troubleshooting.
• Strong communication skills and the ability to work with technical and business stakeholders.
• Experience with workflow orchestration tools such as Apache Airflow or Cloud Composer is preferred.
• Familiarity with infrastructure as code and CI/CD practices is a plus.
• Experience with forecasting, optimization methods, and deploying or monitoring machine learning models is desirable.

Requirements

• Design, develop, and maintain ETL/ELT pipelines that ingest and transform data from databases, APIs, and scheduled SFTP file deliveries.
• Build and manage GCP data infrastructure that meets business requirements for performance, scalability, availability, and security.
• Integrate data across on-premises and cloud environments, supporting both scheduled batch processing and incremental data loads.
• Develop well-structured data models and curated datasets for analytics, reporting, and downstream applications.
• Implement data quality checks, pipeline monitoring, error handling, and recovery processes to ensure accurate and timely data delivery.
• Improve existing data processes by automating manual tasks, optimizing SQL and pipeline performance, and managing cloud resource costs.
• Collaborate with business, product, analytics, and leadership teams to translate requirements into practical data solutions and resolve technical issues.
• Enable analysis of key business metrics, including operational efficiency and customer acquisition.
• Develop and operationalize machine learning models for forecasting and route optimization in collaboration with business and analytics teams.
• Maintain documentation for data pipelines, architecture, source integrations, and operational procedures.

Benefits

• Medical, dental, and vision insurance
• Life and short- and long-term disability coverage
• 401(k) retirement savings plan with company match
• Flex vacation in states other than CA, CO, IL, MA, MT, and NE, with accruals up to 96 hours for first year of employment with tenure-based increases up to 160 hours
• Two (2) floating holidays per year
• Paid sick leave*
• Six (6) paid company holidays
• Two (2) weeks paid pregnancy disability leave, four (4) weeks paid parental bonding leave
• Additional wellness and employee assistance programs