The Insights & Advisory team at Cox Automotive is seeking a highly skilled and forward-thinking Senior Data Engineer to design, build, and optimize data architecture and pipelines that power strategic decision-making across the enterprise. This role combines deep technical expertise with a strong focus on data quality and integrity, ensuring that data is accessible, trusted, and actionable for internal teams and automotive OEM clients.
You'll play a critical role in shaping the data infrastructure roadmap, enabling advanced analytics through AI, machine learning, and big data technologies, while embedding rigorous testing and validation practices into every stage of the data lifecycle.
Key Responsibilities:
Data Architecture & Engineering

• Design and implement robust data architectures supporting structured and unstructured data from internal and external sources.
• Build and maintain scalable, secure data pipelines using cloud-based and distributed technologies.
• Establish data structures and routing mechanisms based on business and technical requirements.
• Ensure alignment with enterprise architecture standards and business goals

Data Quality & Automated Testing

• Develop and execute automated test cases to validate ETL workflows, data pipelines, and reporting logic.
• Create regression test suites to ensure ongoing data integrity and system stability.
• Monitor and troubleshoot data anomalies, proactively identifying root causes and implementing fixes.
• Maintain high standards of data quality across all reporting and analytical outputs.

Advanced Data Solutions

• Develop tools and programming to cleanse, organize, and transform data using AI, ML, and big data techniques.
• Automate manual data processes, transforming them into repeatable, scalable capabilities.
• Collaborate on application development projects to evolve database architecture and design.

Data Analysis & Reporting

• Analyze current and historical performance data to identify trends, variances, and opportunities.
• Support dashboard and reporting development using tools like Tableau, Power BI, or Domo.
• Fulfill routine and ad-hoc reporting requests using accepted metrics and methodologies.

Collaboration & Stakeholder Engagement

• Partner with data consumers, project managers, and business stakeholders to define logical and physical database designs for analytics models.
• Collaborate with internal and external data providers to validate data, provide feedback, and customize data feeds and mappings.
• Communicate findings and test results clearly to both technical and non-technical audiences.

Process Improvement & Innovation

• Identify and implement improvements in internal data management and testing processes.
• Influence the data infrastructure roadmap through technical leadership and innovation.
• Contribute to the development of design standards and assurance processes for software, systems, and applications.

Minimum Qualifications

• Bachelor's degree in a related discipline and 4+ years of experience in data engineering or architecture. The right candidate could also have a different combination, such as a master's degree and 2 years' experience; a Ph.D. and up to 1 year of experience; or 16 years' experience in a related field
• Proven experience designing and building data pipelines and architectures in cloud environments (e.g., AWS, Azure, Snowflake).
• Strong programming skills in Python, Scala, or Java, and proficiency in SQL.
• Experience with big data technologies (e.g., Spark, Kafka, Hadoop) and machine learning frameworks.
• Familiarity with ETL processes, data modeling, and data warehousing concepts.
• Experience with automated testing frameworks (e.g., PyTest, Selenium, dbt tests) and data validation techniques.
• Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
• Experience supporting cross-functional teams including Finance, Sales, and Product Development is a plus.

Preferred Skills

• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) for data transformation and predictive modeling.
• Familiarity with data orchestration tools such as Apache Airflow, dbt, or Dagster.
• Hands-on experience with cloud-native data platforms (e.g., Snowflake, AWS Redshift, Azure Synapse).
• Knowledge of data governance and metadata management best practices.
• Experience integrating external data sources and APIs into enterprise data ecosystems.
• Strong understanding of CI/CD pipelines and DevOps practices for data engineering.
• Ability to work in Agile environments and contribute to sprint planning and backlog grooming.
• Exposure to real-time data streaming technologies (e.g., Kafka, Kinesis) is a plus.

Why Join Cox Automotive?
At Cox Automotive, data is at the heart of every decision. As a Sr Data Engineer, you'll be part of a collaborative team that values innovation, precision, and impact. This role offers the opportunity to shape the future of data infrastructure and empower business leaders with trusted, high-quality data solutions.
USD 101,500.00 - 169,100.00 per year
Compensation:
Compensation includes a base salary in the range of $101,500.00 - $169,100.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
Application Deadline: 03/18/2026