Software Engineer III – Data Engineering KYC

JP Morgan Chase; Glasgow; On-site; GBP 62,000 - 102,000; Full time

Job summary

JPMorgan Chase in the United Kingdom seeks a data engineering specialist to help build and scale enterprise-grade data platforms. You will contribute to secure, high-quality production code for data-intensive applications and mentor engineers.

The role emphasizes collaboration across teams, architectural leadership, and driving innovation with modern data technologies such as Databricks, Snowflake, Spark/PySpark, and LLM orchestration. Cloud experience (AWS/Azure/GCP) is essential.

Qualifications

• Hands-on experience delivering system design at enterprise scale.
• Experience with Python and/or PySpark.
• Knowledge of software development with cloud, AI/ML, or data engineering.
• Experience with large-scale data processing, microservices, APIs, Kafka, Redis, and observability tools.
• Advanced knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
• Cloud-native experience (AWS, Azure, or GCP).
• Ability to communicate with senior leaders; collaborative teamwork.
• Strong problem-solving and analytical skills; adaptable in fast-paced environments.
• Interest in Databricks, Snowflake, Spark/PySpark, Iceberg, and LLM orchestration is a plus.

Responsibilities

• Develop secure, high-quality production code for data-intensive applications.
• Review code and mentor engineers.
• Create durable reusable frameworks and patterns for use across teams.
• Drive adoption of advanced technical methods and best practices.
• Advise cross-functional teams on technological matters.
• Enhance automation at scale to improve value and efficiency.
• Lead architectural decisions across multiple teams.
• Collaborate with stakeholders to deliver impactful solutions.
• Champion best practices in software development and data engineering.
• Support culture of innovation, inclusion, and continuous improvement.

Skills

Python

PySpark

Data engineering

Spark

API design

Kafka

Redis

Cloud

AWS

Azure

GCP

Tools

Databricks

Snowflake

Apache Iceberg

Airflow

Temporal

Dynatrace

Splunk

Grafana

Job description

Salary: £62,000 - 102,000 per year

Requirements:

• We have hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale.
• We have expertise in Python and/or PySpark.
• We have knowledge of software application development and technical processes, with depth in disciplines such as cloud, AI/ML, or data engineering.
• We have experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal).
• We have advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
• We have practical cloud-native experience (AWS, Azure, or GCP).
• We can present and communicate effectively with senior leaders and executives.
• We are committed to inclusive, collaborative teamwork.
• We have good problem-solving and analytical skills.
• We are adaptable in a fast-paced environment.
• We focus on delivering secure and scalable solutions.
• Preferred: we have experience with modern data platforms such as Databricks or Snowflake.
• Preferred: we have deep hands-on experience with Spark/PySpark and other big data processing technologies.
• Preferred: we have expertise in open-source table formats and catalog services such as Apache Iceberg.
• Preferred: we have experience with LLM orchestration frameworks and model serving infrastructure or managed endpoints (AWS Bedrock, Azure OpenAI).
• Preferred: we are familiar with emerging technologies in data engineering.
• Preferred: we can drive innovation and continuous improvement.
• Preferred: we have a passion for mentoring and developing others.

Responsibilities:

• We develop secure, high-quality production code for data-intensive applications and platforms.
• We review code and mentor engineers to foster growth and excellence.
• We create durable, reusable software frameworks and patterns for use across teams.
• We drive adoption of advanced technical methods and industry-standard practices.
• We advise cross-functional teams on technological matters within our domain.
• We apply knowledge of tools within the Software Development Life Cycle, including AI-assisted development and automation.
• We enhance automation at scale to improve value and efficiency.
• We lead architectural decisions and engineering practices across multiple teams.
• We collaborate with stakeholders to deliver impactful solutions.
• We champion best practices in software development and data engineering.
• We support a culture of innovation, inclusion, and continuous improvement.

Technologies:

• AI
• Airflow
• API
• AWS
• Azure
• Big Data
• Cloud
• Databricks
• Dynatrace
• GCP
• Grafana
• Support
• Kafka
• LLM
• Marketing
• Model Serving
• NoSQL
• Python
• PySpark
• Redis
• Snowflake
• Spark
• Splunk
• microservices

More:

We are JPMorgan Chase, a global leader in financial services, providing strategic advice and products to prominent corporations, governments, wealthy individuals, and institutional investors. In our Corporate Sectors agile data engineering team, we are building a trusted Global Know Your Customer (KYC) and Risk Assessment Data Platform. We work across multiple teams to define architecture and engineering standards and deliver high-impact software that scales. We offer a collaborative, inclusive environment where our people are our strength, and we value diversity, reasonable accommodations, and continuous improvement. Our Corporate Functions span finance, risk, human resources, marketing, and other essential areas that help set our businesses, clients, customers, and employees up for success.

last updated 36 week of 2026