Remote Senior Data & Analytics Engineer

Lanter Delivery Systems, LLC; Des Peres (MO); Remote; USD 165,000 - 175,000; Full time

Job summary

Lanter Delivery Systems, a national logistics company, seeks a Senior Data & Analytics Engineer to develop and maintain our enterprise data platform in Azure/Databricks. You will build ETL/ELT pipelines, integrate data sources, and deliver reporting-ready datasets while implementing automated testing to ensure data quality.

You will work across data engineering, analytics, governance, and reporting, partnering with business stakeholders to translate complex requirements into scalable data

Qualifications

• 5+ years in data engineering, analytics engineering, BI engineering, or related field.
• Hands-on with production pipelines using Python and Spark/PySpark.
• Advanced SQL skills with Databricks, Azure Data Lake, and Azure DevOps or comparable tools.

Responsibilities

• Build and operate ETL/ELT pipelines using Databricks, SQL, Python, Spark/PySpark, and Azure Data Lake.
• Develop enterprise gold-layer models spanning source systems and operating units.
• Create data marts with appropriate grain, keys, and slowly changing dimensions.
• Implement automated regression testing to validate pipelines and transformations.
• Own orchestration, observability, and cost management for production solutions.
• Collaborate with stakeholders to define data requirements, governance, and ownership.

Skills

Python

SQL

Databricks

Spark/PySpark

Data modeling

Communication

Independent ownership

Tools

Databricks

Azure Data Lake

Azure DevOps

Git

CI/CD

Job description

Lanter Delivery Systems, a national logistics company, seeks a Senior Data & Analytics Engineer to develop and maintain our enterprise data platform in Azure/Databricks. You will build ETL/ELT pipelines, integrate data sources, and deliver reporting-ready datasets while implementing automated testing to ensure data quality.

You will work across data engineering, analytics, governance, and reporting, partnering with business stakeholders to translate complex requirements into scalable data