Software Engineer II, Data

Credit Acceptance

. Design and build end-to-end data pipelines across batch and streaming architectures .

Posted 10/23/2026full-timeUnited StatesJuniorMid-Level💰 $126,723 - $177,413 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data pipelines, with a strong focus on data quality, governance, and integration strategies. Proficient in programming languages such as Python and SQL, and experienced in leveraging cloud services and data engineering frameworks.

Highest-signal resume keywords

Data Engineering ExperiencePython ProgrammingSQL Database ManagementApache SparkAWS Data Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignData ModelingDatabase ManagementBatch ProcessingStreaming ArchitecturesUnit TestingData Quality FrameworksAI ToolsCI/CD PipelinesAutomated Testing

Soft Skills

Strong Communication SkillsStakeholder CollaborationProblem SolvingContinuous LearningInnovative Thinking

Tools & Technologies

DatabricksApache SparkAirflowDbtLambdaS3GlueMSKDagster

Industry Keywords

Data GovernanceData QualityData IntegrationData LineageComplianceBusiness Processes

Tech Stack

Tools & technologies

AirflowApacheAWSCloudNoSQLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and build end-to-end data pipelines across batch and streaming architectures
Process structured, semi-structured, and unstructured data with emphasis on quality, scalability, reliability, and observability
Partner with stakeholders to understand data requirements and implement data integration strategies
Write unit tests and validate data against acceptance criteria
Apply and advocate for coding, documentation, and testing standards
Conduct impact analysis to assess changes across applications
Develop understanding of business processes to align technical solutions with business needs
Experiment with ideas, validate assumptions, and recommend solutions
Participate in code reviews and communicate application changes
Document code and projects, including reading, writing, and reviewing design documents
Troubleshoot production issues and propose effective solutions
Engage in continuous learning to improve design, code quality, and domain knowledge
Operate with full autonomy on large-scale, complex data projects and serve as a go-to for a data domain
Anticipate edge cases, performance bottlenecks, and data quality risks
Challenge the status quo and contribute innovative solutions
Connect technical work to business value
Remain compliant with policies, processes, and legal guidelines
Perform other duties as assigned
Meet department attendance requirements

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Systems, or related field; or equivalent work experience
Minimum 2 years of data engineering experience
Solid grasp of programming (Python, SQL, Pyspark, etc.), data modeling, and database management (SQL/NoSQL)
Experience designing scalable batch and/or streaming data pipelines
Strong understanding of data modeling
Familiarity with data governance, lineage, and quality frameworks
Fluency with AI tools and ADLC
Working knowledge of Databricks
Experience with Apache Spark
Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan, area; the greater Bellevue, Washington, area; or the San Francisco Bay Area, California
Required degrees must have been earned at institutions of Higher Education which are accredited by the Council for Higher Education Accreditation or equivalent
Preferred: Hands-on experience with AWS data services (e.g., S3, Glue, Lambda, MSK)
Preferred: Proficient in CI/CD pipelines, automated testing, code quality enforcement, and environment management for production-grade data systems
Preferred: Experience in orchestration and transformation frameworks such as Airflow, dbt, and Dagster, along with cloud-native platforms like Databricks
Knowledge of data engineering edge cases, performance bottlenecks, and data quality risks
Strong communication skills, both verbal and written, across all levels

Benefits

Comp & perks

Annual variable incentive of cash and equity between 7.5–15% of base salary
401(K) match
Adoption assistance
Parental leave
Tuition reimbursement
Comprehensive medical, dental, and vision benefits
Two work-from-home days each week
Many nonstandard benefits