Senior Data Engineer - Debt Solutions - San Diego, CA Job Description The Debt Solutions Team is growing quickly, andwerelooking for aSeniorDataEngineerto help accelerate our growth. This role willbe responsible forhelpingbuild outsitewide tracking architectureandthen feeding that data into user-friendly KPI dashboards which track site performanceandproductusage andprovideday-to-dayinsightsintoconsumer behavior. This individual will help buildand deliverthedataengineeringarchitectureforDebt Solutions and work across all departments to provide analysis and insights for future growth. You willbe partof variousaspects of our data management, ranging from designing andmaintainingautomated data infrastructure anddeliveringDataengineeringand Analyticssolutions tofacilitatingdata access and analysis for key company teams. Our team in San Diego plays a key role in the development of these industry-leading products.Werea full-stack product development organization, with front end, back end,dataand machine learning engineering roles, building great products with modern tools and technology. This positionis located inSan Diego, CAand offers a schedule of Monday to Thursday intheoffice and work from home onFridays. Responsibilities: - Design and Oversee implementation of dimensional modeling, database design, and cloud data platform structures (e.g., Databricks, Snowflake,BigQuery) - Develop data platform framework to build secure data warehouses and datalakehousesapplying principles of Medallion Architecture - Design, develop, andmaintainscalable data pipelines and ETL processes using Databricks, Snowflake, and other AWS services - Implement andoptimizeSpark jobs, data transformations, and data processing workflows in Databricks - Building and deploying AI/ML models: Integrate Machine Learning into data pipelines, leverage Databricks ML and AWSML to develop predictive models and drive business insights - Define and Apply AI-assisted software development practices to improve engineering productivity and code quality - Understandvarious data domains and be able totranslate themthrough data transformationsto suit various business needs - Oversee automated data infrastructure: Collaborate with software engineering and product teams to streamline data tracking in our products - Ability to integrate data from disparate sources via cross domain data stitch into existing data model - Implement data governance, lineage tracking, testing, and monitoring frameworks to guarantee data integrity - Hands-on data optimization and query performance - Liaise with key company teams(DBA, DevOps, SecOps) for data accessibility and analysis - Mentor and manage engineers and analysts in the normal execution of their responsibilities. - Successfully implement software development projects to specification and within scheduled timelines and budget parameters - LeverageAWSDevOps and CI/CD best practices to automate the deployment, through terraform,and management of data pipelines and infrastructure. Basic Qualifications: - Bachelor's degreerequiredfrom an accredited, not-for-profit, in-person college/university - A track recordof commitment to prior employers - 6+ years of hands-on experience in software development, delivering high-quality solutions - Strengthin Data Engineering, with strongproficiencyin Python,PySpark, and SQL - Solid foundation in Object-Oriented Programming principles and best practices - Demonstrated success in building and launching data-driven productsoperatingat terabyte scale - Proven record of designing and implementing Enterprise Level secure, andaccurateData platform - Ability to translate technical requirements into robust architecture, data models, and ETL strategies - Practical experience with cloud-based databases, including both relational and non-relational systems - Knowledge of business intelligence software (i.e.Power BIor similar tools) - Understanding of AI technologies and hands-on experienceleveragingAI tooling in development (Claude Code, GitHub Copilot, Cursor, Gemini, Grok) - Ability to retrieve, synthesize, and present critical data instructuresthat isimmediatelyuseful to answeringspecificad-hocquestions - Hands-on data experience on optimization, data quality checks, dataaccuracyand query performance improvement Preferred Qualifications: - Hands-on experience or familiarity with big data platforms such as Databricks or Snowflake - Proficiencywith cloud platforms, including AWS or Azure - Experience working with NoSQL databases (e.g., DynamoDB) and object storage systems (e.g., Amazon S3, GCS, etc.) - Practical knowledge of event streaming technologies, especially Kafka - ExperienceleveragingAWS compute and container services for scalable solutions - Familiarity with large language models (LLMs), prompt engineering, or agent-based architectures - Great analytical and problem-solving skills, with the ability to tackle complex technical challenges - Strong Ability to understandtechnicalchallenges and complex designs, andcommunicateinto simple business ideas, or solutionswith senior management/stakeholders