At a Glance
- Tasks: Design and develop data solutions while collaborating with an agile team.
- Company: Join JPMorgan Chase, a global leader in financial services.
- Benefits: Competitive salary, diverse work environment, and opportunities for growth.
- Other info: Embrace diversity and inclusion in a supportive workplace.
- Why this job: Make a real impact in data engineering and enhance your skills.
- Qualifications: Experience with SQL, Python, AWS, and a passion for data.
The predicted salary is between 50000 - 70000 £ per year.
You thrive on diversity and creativity, and we welcome individuals who share our vision of making a lasting impact. Your unique combination of design thinking and experience will help us achieve new heights.
As a Data Engineer II at JPMorganChase within the Corporate & Investment Bank organization, you are part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As an emerging member of a data engineering team, you execute data solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
- Day-to-day support of JPMC's Adabas & Natural Systems in a data-sharing environment.
- Organises, updates, and maintains gathered data that will aid in making the data actionable.
- Uses enterprise-authorized AI capabilities within the work environment to accelerate data analysis support and technical documentation (e.g., clarifying requirements and drafting data definitions), validating outputs and handling data according to sensitivity and security requirements.
- Applies reuse-first, AI-assisted approaches to improve data quality checks and model/change validation routines, ensuring results are validated and aligned to resiliency and security expectations.
- Demonstrates basic knowledge of the data system components to determine controls needed to ensure secure data access.
- Updates logical or physical data models based on new use cases with minimal supervision.
- Performance & capacity monitoring, tuning and management.
- Incident and problem management, root cause analysis and resolution.
- Application development team support - advisory, consultancy.
- Basic knowledge of the data lifecycle and data management functions.
- Significant experience with statistical data analysis and ability to determine appropriate tools to perform analysis.
- Working knowledge of using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted outputs (e.g., query suggestions or model change summaries) before use, escalating when uncertain and following data handling requirements.
- Familiarity with Microsoft Office products, ServiceNow, Zoom, Outlook, Symphony.
- Natural, Cobol or REXX programming language and design technique skills would be beneficial.
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 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.
Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (SQL/Python/AWS) in Bournemouth
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like J.P. Morgan when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like J.P. Morgan.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like J.P. Morgan.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through J.P. Morgan’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Engineer (SQL/Python/AWS) in Bournemouth
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at J.P. Morgan, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at J.P. Morgan aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at J.P. Morgan
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
