Senior Data Engineer

Point Predictive; San Diego (CA); On-site; USD 140,000 - 160,000; Full time

Benefits offered by this job

401(k)

Flexible spending account

Health insurance

Health savings account

Life insurance

Paid time off

Vision insurance

Job summary

Point Predictive is seeking a Senior Data Engineer in San Diego to design, build, and operate scalable data pipelines feeding core products. You will handle high-volume ingestion, batch and streaming workflows, and data infrastructure across lenders, applications, and transactions.

You will collaborate with Data Science, Product, and Engineering teams to ensure reliable, production-grade systems and models, leveraging AI-assisted development tools to improve velocity, testing, and quality.

Qualifications

• 5+ years of data engineering or software engineering in production systems.
• Hands-on with Python, SQL, dbt, PostgreSQL, Snowflake, AWS.
• Experience designing ETL/ELT, batch and streaming pipelines.
• Familiarity with event-driven technologies like Kafka, Kinesis, Spark Streaming.
• Strong data modeling, distributed systems, testing, observability, and debugging.
• Ability to lead large technical projects across cross-functional teams.
• Experience in financial services or fraud detection is a plus.

Responsibilities

• Design, build, and operate scalable data pipelines for large datasets.
• Develop batch and real-time data processes supporting fraud detection and risk decisioning.
• Build and maintain data transformations with dbt, SQL, Python, Snowflake, PostgreSQL, AWS.
• Improve scalability, reliability, and performance of the data platform.
• Create streaming pipelines using Kafka, Kinesis, Spark Streaming, or similar tools.
• Translate complex data logic into reliable production software.
• Implement testing, monitoring, alerting, and data-quality controls.
• Maintain well-governed data models for downstream products and ML systems.
• Investigate and fix production data issues with root-cause analysis.
• Collaborate with Engineering, Data Science, Product, and customers on large projects.

Skills

5+ years data engineering

Python

SQL

dbt

PostgreSQL

Snowflake

AWS

ETL/ELT pipelines

Event-driven streaming

Distributed systems

Education

Bachelor's or Master's

Tools

Kafka

Kinesis

Spark Streaming

Job description

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 growManual 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

• 401(k)
• 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