Senior Data Engineer

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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Experience with AI/ML frameworks (e.g., Tensor Flow, 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…