Data Engineer - Remote/Hybrid Data Pipelines & Analytics

Socket.dev; Delafield (WI); Hybrid; USD 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid/Remote work flexibility

Job summary

Evans Transportation is seeking a Data Engineer to design, build, and maintain data pipelines powering analytics, reporting, and data-driven decision-making. You will own the pipelines that move data from source systems into clean, well-modeled datasets used by analysts and data scientists.

This role emphasizes data quality, observability, and collaboration with cross-functional teams, with hybrid/remote flexibility and a focus on scalable data infrastructure.

Qualifications

• 3+ years of experience in data engineering or a closely related role.
• Strong SQL and programming knowledge, preferably .NET and Python.
• Solid understanding of data modeling, dimensional modeling, warehousing concepts, and distributed data systems.
• Strong problem-solving skills and focus on data quality.

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines (ETL/ELT).
• Model data in warehouses and lakehouses to support analytics use cases.
• Integrate data from databases, APIs, third-party platforms, and event streams.
• Ensure data quality, reliability, and observability through testing, monitoring, and alerting.
• Optimize pipeline and query performance and manage cost and scalability of data systems.
• Implement and enforce data governance, security, and access-control best practices.
• Collaborate with analysts, data scientists, and software engineers to deliver usable data products.
• Document data flows, schemas, and processes to keep the platform maintainable.

Skills

SQL

.NET

Python

Tools

Airflow

Dagster

dbt

Azure

Terraform

Docker

Git

Job description

Evans Transportation is seeking a Data Engineer to design, build, and maintain data pipelines powering analytics, reporting, and data-driven decision-making. You will own the pipelines that move data from source systems into clean, well-modeled datasets used by analysts and data scientists.

This role emphasizes data quality, observability, and collaboration with cross-functional teams, with hybrid/remote flexibility and a focus on scalable data infrastructure.