Senior Data Engineer - Risk Platform & Databricks Pipelines

Next Frontier Capital; Plano (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Tuition reimbursement

Job summary

JPMorgan Chase & Co. is seeking a Senior Associate Data Engineer to help design and modernize the risk feature engineering platform within Corporate Technology Risk. You will build scalable batch and streaming pipelines, apply governance controls, and collaborate with data scientists and engineers.

You will migrate legacy workloads to Databricks-native architectures, implement CI/CD, automate testing, and leverage enterprise AI-assisted tools to boost productivity and quality.

Qualifications

• Formal training or certification in software engineering, computer science, data engineering, or related discipline with 3+ years of applied industry experience.
• Hands-on experience with Databricks, Apache Spark, PySpark, Delta Lake, and modern Lakehouse architectures.
• Experience building and supporting large-scale batch and streaming data pipelines.
• Proficiency in Python and SQL with a strong understanding of distributed computing principles.
• Hands-on experience using enterprise-authorized AI-assisted software development tools with evaluation of AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows and secure handling of data.
• Working knowledge of Databricks Unity Catalog, Delta Live Tables, and modern declarative pipeline frameworks.
• Experience with AWS services including S3, Glue, EMR, Lambda, ECS/EKS.

Responsibilities

• Design, develop, and support scalable feature engineering solutions on Databricks for risk analytics and ML.
• Build and maintain reusable batch and real-time feature pipelines with onboarding, versioning, and monitoring.
• Implement data engineering solutions using Databricks, Spark, PySpark, Delta Lake, Lakeflow; ensure scalability and maintainability.
• Drive platform modernization by migrating legacy Spark/EMR workloads to Databricks-native architectures.
• Apply software engineering best practices including CI/CD, testing, reviews, observability, and production support.
• Leverage AI-assisted tooling to accelerate development and automate SDLC activities.
• Apply data quality, governance, lineage, and security controls in regulatory contexts (PCI, etc.).
• Develop cloud-native solutions on AWS (S3, Glue, Lambda, ECS/EKS, Aurora/RDS) and IaC (Terraform).
• Participate in architecture reviews and decision-making to improve performance, stability, and cost efficiency.
• Collaborate with data scientists and engineers; mentor juniors and promote reuse-first practices.

Skills

Databricks

Apache Spark

PySpark

Delta Lake

Lakehouse architectures

Python

SQL

AWS

CI/CD

AI-assisted tools

Education

Bachelor's degree in CS/Engineering

Tools

Terraform

GitHub Copilot

Unity Catalog

Delta Live Tables

Airflow

Job description

JPMorgan Chase & Co. is seeking a Senior Associate Data Engineer to help design and modernize the risk feature engineering platform within Corporate Technology Risk. You will build scalable batch and streaming pipelines, apply governance controls, and collaborate with data scientists and engineers.

You will migrate legacy workloads to Databricks-native architectures, implement CI/CD, automate testing, and leverage enterprise AI-assisted tools to boost productivity and quality.