Credit Acceptance is an award-winning company recognized for its workplace culture and success in the used car finance industry. The Staff Software Engineer, Data will design, build, and scale data pipelines while collaborating with cross-functional teams to optimize data integration and support business processes.
Responsibilities:
- Design, build, and scale data pipelines across a variety of source systems and streams, including internal, third-party, and cloud-based platforms
- Interface with cross-functional teams to extract, load, and transform data using cloud-native data engineering principles
- Collaborate with stakeholders to understand data requirements and develop efficient strategies for data acquisition and integration
- Write unit-tests and validate your software against acceptance criteria
- Evolve and transform the design and architecture of applications towards leading edge technologies and practices
- Author, apply and advocate for team coding, documenting and testing standards
- Conduct impact analysis to proactively identify impact of a change across multiple applications
- Learn the business process domain to better support the business and align technologies with the business process
- Experiment and test ideas, validate assumptions against needs, reach conclusions and recommend solutions
- Lead code reviews and communicate application changes
- Document code and projects so others can easily understand, maintain and support
- Debug the problems which arise in production and propose effective solutions within the application and across multiple applications
- Read, write and review design documents
- Contribute to team's sprint commitments and actively participate in our Agile practices, including recommendations for process improvement
- Lead continuous learning activities to improve design and code quality as well as to increase application domain knowledge
- Participate in the talent selection process
Requirements:
- Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience
- Minimum 8 years of software engineering experience or comparable depth of experience, with recent experience building on cloud data platforms
- Experience in the lead role overseeing technical direction of a team of data engineering talent
- Strong understanding of one or more programming languages commonly used in data engineering (e.g., Python, Java, Scala)
- Practical experience in Software Development Life Cycle (SDLC) including Agile/SCRUM and Waterfall
- Experience designing scalable batch and streaming pipelines
- Strong understanding of data modeling, schema design, and lakehouse principles
- Experience with data governance, lineage, and quality frameworks
- Experience working on mission-critical enterprise-class applications
- Demonstrated ability to coach and mentor less experienced team members
- Expertise in Apache Spark
- Strong working knowledge of Databricks (e.g., Delta Lake, Unity Catalog, DLT, Auto Loader)
- Hands-on experience with AWS data services (e.g., S3, Glue, Lambda, MSK)
- Financial services or FinTech industry experience