Data Engineer II — Cloud Analytics & Pipelines

CAI Cox Automotive Corp Svcs., LLC; Indianapolis (IN); Hybrid; USD 89,000 - 134,000; Full time

Benefits offered by this job

Competitive salary

Bonus program

Healthcare options

401(k) match

Job summary

Cox Automotive is seeking a Data Engineer II to design, build, and optimize scalable data pipelines and enterprise data models. You will partner with engineers, analysts, and stakeholders to deliver analytics-ready data assets and data products that drive business outcomes.

You will work in a modern cloud data platform, leveraging Snowflake, dbt, and other cloud tools. A hybrid schedule and opportunities to evolve data practices are offered.

Qualifications

• 2+ years in data engineering or related field.
• Experience with data warehouse or analytics ETL workflows.
• SQL proficiency for data transformation and analytics.
• Experience with cloud-based data platforms.
• Familiarity with source control and collaborative development.

Responsibilities

• Design and deliver scalable data pipelines and integration solutions for analytics.
• Develop enterprise data models and warehouse solutions for reporting.
• Collaborate with stakeholders to translate requirements into data products.
• Lead performance improvements and automate operations.
• Mentor engineers and evaluate new data technologies.

Skills

SQL

Python

Cloud platforms

ETL processes

Data modeling

Data warehousing

Data products

Code reviews

Education

Bachelor's degree in Computer Science / Information Systems / Engineering / Mathematics / Data Analytics

Tools

Snowflake

dbt

Microsoft Fabric

Azure

AWS

Job description

Cox Automotive is seeking a Data Engineer II to design, build, and optimize scalable data pipelines and enterprise data models. You will partner with engineers, analysts, and stakeholders to deliver analytics-ready data assets and data products that drive business outcomes.

You will work in a modern cloud data platform, leveraging Snowflake, dbt, and other cloud tools. A hybrid schedule and opportunities to evolve data practices are offered.