Note: The job is a remote job and is open to candidates in USA. Lanter Delivery Systems is a national logistics company specializing in overnight, unattended delivery of automotive, agricultural, and industrial parts. The Senior Data & Analytics Engineer develops and operates enterprise data pipelines and models in Azure and Databricks, while supporting analytics, reporting, governance, testing, and data platform reliability. The role partners with business and technical stakeholders to deliver scalable, accurate data solutions and provides technical guidance on complex data and analytics needs.
Responsibilities
- Build and operate ETL/ELT pipelines using Databricks, SQL, Python, Spark/PySpark, and Azure Data Lake
- Develop an integrated enterprise gold-layer model spanning source systems, customers, and operating companies
- Build dimensional serving-layer and data-mart models with deliberate decisions regarding grain, keys, conformed dimensions, historical data, and slowly changing dimensions
- Implement automated regression testing using defined inputs and expected outputs to validate pipelines and transformations
- Own orchestration, observability, performance, failure diagnosis, replay and recovery, root-cause fixes, and cost management for assigned production solutions
- Partner with stakeholders to reconcile business definitions and establish data requirements, rules, ownership, and governance standards
- Apply disciplined engineering practices, including Git, code review, reusable components, automated testing, controlled deployments, and technical documentation
- Develop analytics and reporting solutions using Sigma, Power BI, or comparable platforms
- Support strategic data initiatives across Lanter’s business units and industry verticals, including AI, operational visibility, and analytics enablement
- Independently own deliverables and provide technical guidance on complex data and analytics needs
Skills
- 5+ years of experience in data engineering, analytics engineering, BI engineering, or a related field
- Strong, recent, hands-on experience developing production pipelines with Python and Spark/PySpark
- Advanced SQL skills and hands-on experience with Databricks, Azure Data Lake, and Azure DevOps or comparable technologies
- Experience designing integrated enterprise models and dimensional data marts, including grain, keys, conformed dimensions, history, and slowly changing dimensions
- Experience implementing automated testing, regression testing, data-quality controls, and pipeline validation
- Experience operating production data solutions, including monitoring, optimization, troubleshooting, recovery, and cost management
- Experience with Git, code review, CI/CD, reusable development practices, and technical documentation
- Ability to translate complex business requirements into scalable data and analytics solutions
- Strong communication, collaboration, problem-solving, and independent ownership skills
- This is a full-time, remote position
- Travel may be required periodically for company meetings, training, or other business needs
- The team member may be required to sit for extended periods of time while working at a computer and communicating with internal and external business partners
- The team member is regularly required to listen, communicate verbally and in writing, sit for extended periods of time, use a computer and other office equipment, and occasionally lift up to 15 pounds at a time
- Experience in logistics, transportation, supply chain, or another operationally complex environment
- Experience supporting data governance, AI, or advanced analytics initiatives
- Proximity to Lanter's St. Louis headquarters is preferred
Benefits
- This is a full-time, remote position.
- There is no regular onsite work requirement.
Company Overview
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