For well over a century, Cox Enterprises has been shaping the future with daring ideas and values-driven thinking. Since our founding in 1898, our relentless spirit of innovation has driven us to disrupt industries and enhance the quality of life in the communities we serve. Through our major divisions — Cox Communications, Cox Automotive and Cox Farms — our people have countless opportunities to grow and make an impact in the communications and automotive industries, as well as in new ventures in agriculture, cleantech, digital media and more. As a privately-held, family-owned business, we know that people are our most valuable asset. We offer a supportive and inclusive environment with flexible career growth, amazing benefits and work-life balance at the forefront. Our mission, our ways of working and our commitment to people are what make our workplace culture remarkably flexible and resilient. Join us to build a better future and make your mark.
Senior Data Engineer
Location
United States
Posted
4 days ago
Salary
$101K - $169K / year
No structured requirement data.
Job Description
Company
Cox Automotive - USAJob Family Group
Job Profile
Management Level
Flexible Work Option
Travel %
Work Shift
Compensation
Compensation includes a base salary 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.Job Description
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.
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