Senior
Join us to shape the future of financial technology and make a meaningful impact on millions of customers worldwide.
As a Software Engineer at JPMorgan Chase in the Corporate Sector’s agile data engineering team, you will promote the development of a trusted Global Know Your Customer (KYC) and Risk Assessment Data Platform. You will work across multiple teams, define architecture and engineering standards, and deliver high-impact software that scales. You’ll collaborate with colleagues to implement secure, stable, and scalable solutions, and help shape the team’s culture and technical direction. Your expertise will support the firm’s portfolios and contribute to our ongoing success.
Job responsibilities
Develop secure, high-quality production code for data-intensive applications and platforms
Review code and mentor engineers to foster growth and excellence
Create durable, reusable software frameworks and patterns for use across teams
Drive adoption of advanced technical methods and industry-standard practices
Advise cross-functional teams on technological matters within your domain
Apply knowledge of tools within the Software Development Life Cycle, including AI-assisted development and automation
Enhance automation at scale to improve value and efficiency
Lead architectural decisions and engineering practices across multiple teams
Collaborate with stakeholders to deliver impactful solutions
Champion best practices in software development and data engineering
Support a culture of innovation, inclusion, and continuous improvement
Required qualifications, capabilities, and skills
Hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale
Expertise in Python and/or PySpark
Knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering
Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance
Practical cloud-native experience (AWS, Azure, or GCP)
Ability to present and communicate effectively with senior leaders and executives
Commitment to inclusive, collaborative teamwork
Good problem-solving and analytical skills
Adaptability in a fast-paced environment
Focus on delivering secure and scalable solutions
Preferred qualifications, capabilities, and skills
Experience with modern data platforms such as Databricks or Snowflake
Deep hands-on experience with Spark/PySpark and other big data processing technologies
Expertise in open-source table formats and catalog services such as Apache Iceberg
Experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI)
Familiarity with emerging technologies in data engineering
Ability to drive innovation and continuous improvement
Passion for mentoring and developing others
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