n Build the data foundation behind a digital investing experience used by over 275,000 investors in the UK. Join Personal Investing to help deliver clear, data-driven insights through robust cloud-native platforms and pipelines. This is an opportunity to grow your impact on a platform that supports analytics and regulatory reporting at scale.
As a Data Engineer at JPMorgan Chase within Personal Investing, you will build and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-promoten applications at scale. You will help us deliver reliable, scalable, observable, and secure data solutions across cloud-native services, lakehouse architectures, data warehousing, and streaming systems. You'll partner with teammates to build consistent, maintainable pipelines and contribute across the software delivery lifecycle from requirements through support.
\Build and maintain scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt
Build and operate batch and streaming data pipelines with strong scalability, performance, and fault tolerance
Develop and manage workflow orchestration using tools such as Apache Airflow to support reliable, observable, and well-scheduled data movement and transformations
Implement and optimize data models and warehouse structures to support analytics and business intelligence workloads
Write clean, testable Python/PySpark code using object-oriented principles and unit testing
Implement infrastructure-as-code for the data platform using Terraform
Contribute across the software development lifecycle, including requirements, design, development, testing, deployment, release, and support
Collaborate with teammates in an agile, dynamic environment to deliver reliable outcomes
\Degree in Computer Science or a STEM-related field (or equivalent)
Experience working in an agile and dynamic environment
Experience across the software development lifecycle (requirements, design, architecture, development, testing, deployment, release, and support)
At least 5 years of recent, hands-on professional experience actively coding as a data engineer
AWS, Google Cloud, or Azure)
Experience writing Python using object-oriented programming and unit/integration testing practices
Experience with SQL and familiarity with SQL-based workflow management tools such as dbt
Terraform) for cloud-based data infrastructure
\Data modeling skills
Experience with data streaming and scalable processing frameworks (e.g., Experience automating deployment, releases, and testing in continuous integration and continuous delivery pipelines
Experience designing automated tests (unit, component, integration, and end-to-end), including use of mocking frameworks
Experience with containers and container-based deployment environments (e.g., Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. n for more information about requesting an accommodation.
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing.
or continue with email
As a Data Engineer at JPMorgan Chase within Personal Investing, you will build and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-promoten applications at scale. You will help us deliver reliable, scalable, observable, and secure data solutions across cloud-native services, lakehouse architectures, data warehousing, and streaming systems. You'll partner with teammates to build consistent, maintainable pipelines and contribute across the software delivery lifecycle from requirements through support.
\Build and maintain scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt
Build and operate batch and streaming data pipelines with strong scalability, performance, and fault tolerance
Develop and manage workflow orchestration using tools such as Apache Airflow to support reliable, observable, and well-scheduled data movement and transformations
Implement and optimize data models and warehouse structures to support analytics and business intelligence workloads
Write clean, testable Python/PySpark code using object-oriented principles and unit testing
Implement infrastructure-as-code for the data platform using Terraform
Contribute across the software development lifecycle, including requirements, design, development, testing, deployment, release, and support
Collaborate with teammates in an agile, dynamic environment to deliver reliable outcomes
\Degree in Computer Science or a STEM-related field (or equivalent)
Experience working in an agile and dynamic environment
Experience across the software development lifecycle (requirements, design, architecture, development, testing, deployment, release, and support)
At least 5 years of recent, hands-on professional experience actively coding as a data engineer
AWS, Google Cloud, or Azure)
Experience writing Python using object-oriented programming and unit/integration testing practices
Experience with SQL and familiarity with SQL-based workflow management tools such as dbt
Terraform) for cloud-based data infrastructure
\Data modeling skills
Experience with data streaming and scalable processing frameworks (e.g., Experience automating deployment, releases, and testing in continuous integration and continuous delivery pipelines
Experience designing automated tests (unit, component, integration, and end-to-end), including use of mocking frameworks
Experience with containers and container-based deployment environments (e.g., Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. n for more information about requesting an accommodation.
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing.
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