At a Glance
- Tasks: Build and maintain scalable data platforms for a digital investing experience.
- Company: Join JPMorgan Chase, a leader in financial services with a focus on innovation.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Dynamic, inclusive environment with a commitment to diversity and career development.
- Why this job: Make a real impact on data solutions used by over 275,000 investors.
- Qualifications: Degree in Computer Science or STEM, plus 5 years of hands-on data engineering experience.
The predicted salary is between 60000 - 80000 £ per year.
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. You'll work with modern lakehouse, warehousing, and streaming technologies while strengthening engineering excellence and operational reliability. 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-promoted 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.
Job responsibilities:
- 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.
- Containerize and deploy services using Docker, Kubernetes, and Helm.
- 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.
Required qualifications, capabilities, and skills:
- 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.
- Hands-on experience with major cloud technologies (e.g., 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.
- Experience with orchestration tools such as Airflow (or similar).
- Understanding of messaging/streaming systems such as Kafka or Pub/Sub (or similar).
- Familiarity with infrastructure-as-code (e.g., Terraform) for cloud-based data infrastructure.
Preferred qualifications, capabilities, and skills:
- Data modeling skills.
- Experience with data streaming and scalable processing frameworks (e.g., Spark, Flink, Beam, or similar).
- Experience automating deployment, releases, and testing in continuous integration and continuous delivery pipelines.
- Experience with lakehouse patterns and table formats (e.g., Apache Iceberg).
- Experience with federated query engines such as Trino.
- 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., Docker, Kubernetes, or similar).
We recognise 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, colour, 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.
Data Engineer III employer: Fairygodboss
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Data Engineer III in Personal Investing, you'll have the opportunity to work with cutting-edge technologies while contributing to a platform that serves over 275,000 investors in the UK. We are committed to your professional growth, providing ample opportunities for skill development and career advancement in a diverse and inclusive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer III
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, PySpark, and cloud technologies. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data engineering. Practice common interview questions and be ready to discuss your experience with tools like Airflow and Terraform.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Engineer III
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer III role. Highlight your hands-on experience with Python, cloud technologies, and data pipelines to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data engineering and how your background aligns with our mission at StudySmarter. Share specific examples of your work that demonstrate your expertise in building scalable data solutions.
Showcase Your Projects:If you've worked on relevant projects, don’t hesitate to include them! Whether it’s a personal project or something from your previous job, we want to see how you’ve applied your skills in real-world scenarios.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right team!
How to prepare for a job interview at Fairygodboss
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, PySpark, and SQL. Brush up on your knowledge of cloud platforms like AWS or Azure, and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced as a Data Engineer and how you overcame them. Use examples that highlight your ability to build scalable data pipelines and ensure data quality, as this will demonstrate your hands-on experience.
✨Understand the Agile Environment
Since the role involves working in an agile setting, be prepared to talk about your experience with agile methodologies. Share examples of how you've collaborated with teams and adapted to changing requirements during the software development lifecycle.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about the team’s current projects, the challenges they face, or how they measure success in their data initiatives. This shows you're genuinely interested and engaged.
