Lead Software Engineer [Multiple Positions Available]

JPMorgan Chase & Co.; Tampa (FL); On-site; USD 130,000 - 170,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a seasoned data engineering and ML specialist in Tampa to develop scalable data storage and processing solutions. You will build robust ETL pipelines, integrate with BI platforms, and support real‑time analytics and reporting needs.

You will design and deploy ML models for predictive analytics and fraud detection, using Python and modern frameworks, while ensuring security, governance, and cost efficiency across cloud and on‑prem environments.

Qualifications

• Bachelor's degree in Electrical/Computer Engineering or related field with 7+ years of work experience.
• Proven experience designing and deploying ML/AI solutions in cloud/on‑prem environments.
• Strong data engineering, ETL design, and distributed processing background.

Responsibilities

• Develop and maintain data storage and processing solutions for analytics.
• Build and optimize ETL processes and data pipelines for reliability and performance.
• Design, train, and deploy ML/AI models for fraud detection and analytics.
• Ensure security, governance, and regulatory compliance in cloud/on‑prem setups.

Skills

Python

Machine Learning

Data Engineering

ETL

Distributed Computing

SQL / Data Modeling

Fraud Detection

Terraform

AWS

Serverless

TensorFlow / PyTorch

Education

Bachelor's degree in Electrical/Computer Engineering or related field

Tools

Terraform

AWS

AWS Lambda

Spark

Flink

S3

AWS Glue

Airflow / Orchestration

Job description

DESCRIPTION:

Duties: Develop and maintain data storage and processing solutions to support efficient data management and analytics, utilizing modern cloud and on-premises technologies such as data lakes and distributed databases. Build and optimize applications for data ingestion, transformation, and retrieval, leveraging scalable storage and database platforms. Create automated extract, transform, and load (ETL) processes and optimize data pipelines for reliability and performance using orchestration and data engineering tools. Support complex data analytics and reporting needs by integrating with enterprise data platforms and business intelligence tools. Implement real-time and batch data processing solutions for analytics and machine learning using distributed computing frameworks including Apache, Spark, and Flink. Design, train, and deploy machine learning (ML) and AI models to address business challenges, including predictive analytics and decision support. Develop and maintain models and systems for fraud detection and risk mitigation, ensuring alignment with industry best practices and regulatory requirements. Use infrastructure automation tools to provision, manage, and scale cloud and on-premises resources efficiently. Build and deploy serverless solutions to enable flexible, scalable, and cost-effective application architectures. Implement strategies to monitor, manage, and reduce cloud infrastructure expenses while maintaining performance and reliability. Maintain compliance with relevant regulations and standards, and implement robust data security and governance practices.

QUALIFICATIONS:

Minimum education and experience required: Bachelor's degree in Electrical Engineering, Electronic Engineering, Computer Engineering, Computer Information Systems, or related field of study plus 7 years of experience in the job offered or as Lead Software Engineer, Software Engineer/Developer, Programmer Analyst, Technical Lead, or related occupation.

Skills Required: This position requires experience with the following: Designing, implementing, and optimizing machine learning algorithms and AI solutions using Python; data preprocessing, feature engineering, model selection, and hyperparameter tuning; developing end-to-end ML pipelines, from data ingestion to model deployment and monitoring, to ensure scalability and robustness; architecting and deploying scalable data processing workflows using AWS Glue for ETL, AWS Athena, Step Functions for orchestration, S3, and elastic map reduce for distributed data analytics; designing cloud-native solutions leveraging AWS services with security, cost optimization, and high availability; utilizing cloud data warehousing features to enable complex queries, data modeling, and business intelligence; applying best practices for data validation, cleansing, and governance within cloud data environments; developing and maintaining data models, data lakes, and data warehouses; implementing analytics solutions and optimizing query performance and data flow; authoring and maintaining Terraform scripts to automate cloud infrastructure provisioning and management, repeatability, and compliance; developing and deploying serverless applications and integrating them with AWS Lambda for event-driven processing; building and enhancing fraud detection models, including feature engineering, entity resolution, and real-time scoring by using domain-specific techniques; identifying fraud patterns and translating business requirements into effective ML solutions; developing, validating, and deploying supervised, unsupervised, and reinforcement learning models; evaluating model performance using metrics and implementing strategies for continuous improvement; applying deep learning techniques using TensorFlow, PyTorch, Keras, or Scikit-learn for model development, training, and evaluation.

Job Location: 10410 Highland Manor Dr, Tampa, FL 33610.

Full-Time.