Software Engineer III – Data Engineering- Corporate Know Your Customer

JPMorgan Chase & Co.; Auchentibber; On-site; GBP 60,000 - 120,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Software Engineer for the Corporate Sector’s agile data engineering team to build a trusted Global KYC and Risk Assessment Data Platform. You will define architecture, set engineering standards, and deliver secure, scalable software affecting millions of customers worldwide.

You will collaborate with cross‑functional teams, mentor engineers, and drive best practices across data engines and platforms, shaping the team’s technical direction and culture.

Qualifications

• Hands-on experience delivering data-scale software and services.
• Expertise with Python and PySpark in data engineering.
• Experience with cloud-native architectures (AWS, Azure, or GCP).
• Knowledge of SQL and NoSQL databases, data lakes, and data governance.
• Ability to communicate with senior leaders and cross-functional teams.

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

Skills

Python

PySpark

Cloud platforms

Data engineering

API design

Kafka

Observability tools

Distributed systems

Tools

Databricks

Snowflake

Apache Iceberg

Airflow

Temporal

Kubernetes

Job description

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