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$135,000–$202,561.
Based on 240 similar postings.
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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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1254 open roles
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Software Engineer III - Data Engineering | Infrastructure Platforms serves as a seasoned member of an agile team designing and delivering secure, scalable technology products. The role involves designing, developing, testing, and deploying production-ready applications that combine Java-based software engineering with Python-based AI/ML capabilities. Key responsibilities include translating business requirements into technical solutions, maintaining algorithms, and using SQL to analyze large, heterogeneous datasets. The position requires building metrics reporting and dashboards to support operations management while improving efficiency in cloud and hybrid data environments. Required skills include experience with Spring boot, Hibernate, Jupiter notebooks, and data architectures like Data Mesh or Data Lake. Candidates must also possess knowledge of Retrieval-Augmented Generation, agentic workflows, and telemetry tools like Splunk or Elastic Search to solve complex data engineering problems.
What does a Software Engineer earn in Texas?
Median $173350 from 173 postings across 43 companies.
Translate stakeholder and business requirements into technical solutions, prototypes, and delivery plans.
Develop secure production code and maintain algorithms using Java and Python.
Analyze large datasets using SQL to validate assumptions and measure solution impact.
Design and support scalable, resilient architectures for reliable deployment and monitoring.
Automate operational processes to eliminate recurring issues and improve platform stability.
Create unit and integration tests and participate in regular code reviews.
Produce technical documentation and reports for both technical and non-technical audiences.
Support model and data governance by documenting solution designs for risk and privacy assessments.
What we're looking for
Formal training or certification on software engineering concepts and 3+ years of applied experience.
Hands-on experience in system design, application development (SDLC), testing, and operational stability for enterprise cloud-native applications.
Experience developing, debugging, and maintaining code in large corporate environments using Java, Python, and SQL.
Experience with frameworks such as Spring Boot, Hibernate, and Envers.
Experience with data-intensive applications like Jupyter notebooks and data engineering concepts including BigData, Data Mesh, and Data Lake architectures.
Experience with telemetry systems using tools like Splunk or Elastic Search.
Experience with Retrieval-Augmented Generation (RAG), agentic workflows, prompt engineering, and model development.
Experience with AI-assisted software development tools and understanding of responsible AI use in engineering workflows.
Bachelor’s degree in Computer Science with a specialization (preferred).
Experience with Data Analytics (preferred).
Experience with Oracle or MongoDB (preferred).
Experience deploying vector databases on services like GKE or EKS (preferred).
Python
SQL
AWS
Databricks
PySpark
Machine Learning
Spark
S3
EC2
EMR
CloudWatch
Pandas
Numpy
Data Pipelines
CI/CD
Agile
Apache Airflow
Control M
Big Data
System Design