
Platform Software Engineer III- ETL / AWS/ Python / Pyspark
at J.P. Morgan
Posted 17 days ago
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Senior software engineer on JPMorgan Chase's Asset & Wealth Management Technology team responsible for designing and delivering scalable ETL and data engineering solutions using Python and PySpark on AWS. Build and implement data pipelines, leverage infrastructure-as-code to orchestrate and monitor pipelines, and create programmatic cloud compute resources for large-scale data ingestion and distribution. Produce architecture and design artifacts, write secure production-grade code, and contribute to CI/CD and DevOps practices for data platforms. Role requires strong experience with cloud services (AWS), data modeling, ETL/warehousing, and tools such as Terraform, Snowflake/Databricks, and big data services.
- Compensation
- Not specified
- City
- Jersey City
- Country
- United States
Currency: Not specified
Full Job Description
Location: Jersey City, NJ, United States
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Platform Software Engineer III- ETL / AWS / Python / Pyspark at JPMorganChase within the Asset and Wealth Management Technology Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Designs, develops, and implements scalable data pipelines and ETL batches using Python/PySpark on AWS
- Uses infrastructure as code tools to build applications to orchestrate and monitor data pipelines, create and manage on-demand compute resources on cloud programmatically, and create frameworks to ingest and distribute data at scale
- Stays up-to-date with emerging technologies and industry trends to drive innovation and continuous improvement
Leverage AI coding assist tools to accelerate software development, testing and delivery- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3 + years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in software development and data engineering, with demonstrable hands-on experience in Python and PySpark
- Proven experience with cloud platforms such as AWS, Azure, or Google Cloud
- Good understanding of data modeling, data architecture, ETL processes, and data warehousing concepts
- Experience or good knowledge of cloud native ETL platforms like Snowflake and/or Databricks
- Experience with big data technologies and services like AWS EMRs, Redshift, Lambda, S3
- Proven experience with efficient Cloud DevOps practices and CI/CD tools like Jenkins/Gitlab, for data engineering platforms
- Good knowledge of SQL and NoSQL databases, including performance tuning and optimization
- Experience with declarative infra provisioning tools like Terraform, Ansible or CloudFormation
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Preferred qualifications, capabilities, and skills
- Knowledge of machine learning model lifecycle, AI coding assist tools, and cloud-native MLOps pipelines and frameworks
- Familiarity with data visualization tools and data integration patterns
Seeking a platform engineer with strong experience in Python, Pyspark, ETL and AWS
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