Senior Data Engineer

Overview Point Predictive is redefining fraud detection and risk decisioning for lenders through large-scale consortium data, machine learning, and real-time systems. We are seeking a Senior Data Engineer to help design, build, and maintain the data platforms behind our core products, including high-volume data ingestion, batch and streaming pipelines, real-time decisioning systems, and the data infrastructure that supports models and customer-facing applications across financial institutions. In this role, you will work closely with engineering peers, Data Science, and Product to ensure that data, models, and production systems are seamlessly integrated, reliable, and ready to operate at scale. The ideal candidate brings strong technical depth and execution rigor—a hands-on engineer who takes ownership of the systems they build, raises the bar on quality, and uses modern AI-assisted development tools to improve engineering velocity, testing, and reliability. Responsibilities Design, build, and operate scalable pipelines that ingest and process large volumes of lender, application, and transaction data across a variety of formats and delivery methods Develop batch and real-time data processes that support fraud detection, risk decisioning, model features, customer integrations, and production outputs Build and maintain data transformation workflows using dbt, SQL, Python, Snowflake, PostgreSQL, and AWS Improve the scalability, reliability, and performance of the data platform through architectural improvements, query optimization, and automation Build streaming and event-driven pipelines using technologies such as Kafka, Kinesis, Spark Streaming, or similar platforms Translate complex data-processing, fraud, and business logic into reliable, maintainable production software Implement automated testing, monitoring, alerting, reconciliation, and data-quality controls across critical workflows Maintain clean, well-governed, and well-documented data models for downstream products, analytics, and machine-learning systems Investigate production issues and customer-reported data problems, determine root causes, and implement durable fixes Partner with Software Engineering, Data Science, Product, and customer-facing teams to deliver large-scope technical projects Contribute to data architecture decisions and engineering standards Use AI-assisted development tools, such as Claude Code, to improve productivity, testing rigor, and engineering quality Qualifications 5+ years of data engineering or software engineering experience building and operating scalable production systems Strong hands-on experience with Python, SQL, dbt, PostgreSQL, Snowflake, and AWS Experience designing and supporting production ETL, ELT, batch, and streaming pipelines Experience with event-driven technologies such as Kafka, Kinesis, Spark Streaming, or similar tools Strong understanding of data modeling, distributed systems, testing, observability, and production debugging Demonstrated ability to lead large technical projects and work effectively across Engineering, Data Science, Product, and business teams High level of ownership, accountability, communication, and attention to quality Comfort using AI-assisted and agentic development tools while maintaining strong engineering judgment and review standards Experience in financial services, lending, fraud detection, or risk decisioning is a plus What Success Looks Like Reliable, well-tested batch and real-time pipelines move large volumes of data with minimal production issues Data models are clean, documented, governed, and dependable for downstream systems Monitoring and automated controls identify pipeline and data-quality issues before they affect customers Infrastructure scales efficiently as data volumes, customers, and product use cases grow Manual processes are replaced with durable, automated solutions Production issues and customer requests are resolved quickly and result in lasting improvements Technical projects are delivered with clear ownership and strong cross-functional partnership AI-assisted development tools are used thoughtfully to increase speed, strengthen testing, and reduce errors Why This Role Build and own the data backbone of a company delivering real-time fraud and risk decisions to lenders. This is a high-impact, hands-on role with direct influence on the data that powers Point Predictive’s models, products, and customer decisions. You will work on large-scale ingestion, transformation, streaming, and ETL systems while helping shape the architecture and engineering standards of a growing data platform. You will solve meaningful production challenges, modernize critical systems, and work closely with Engineering and Data Science leaders during a key phase of the company’s growth. Education Bachelor's or Master's Pay: $140,000.00 - $160,000.00 per year Benefits: 401(k) Dental insurance Flexible spending account Health insurance Health savings account Life insurance Paid time off Vision insurance Application Question(s): This is an In Office Job - Can you confirm that you will be available to work in office 5 days a week Our Core Values are: Get it Done, Pitch In, and Be the Expert. Describe in detail how you have embodied those Values in the past and how you will continue to work by them at Point Predictive Ability to Commute: San Diego, CA 92101 (Required) Work Location: In person