At a Glance
- Tasks: Design and deliver innovative data solutions using Python and SQL.
- Company: Join JPMorgan Chase, a leader in the financial services industry.
- Benefits: Career growth opportunities, collaborative culture, and competitive salary.
- Other info: Dynamic team environment focused on excellence and continuous improvement.
- Why this job: Make a real impact on business objectives while driving innovation.
- Qualifications: 3 years of experience in data engineering and strong skills in Python and SQL.
The predicted salary is between 60000 - 80000 € per year.
Are you ready to shape the future of data engineering at JPMorgan Chase? Join a dynamic team where your unique skills will help build innovative solutions and contribute to a winning culture. You’ll have opportunities for career growth, collaborate with talented professionals, and make a real impact on our business objectives. Your expertise will empower our teams and drive success across the firm.
As a Data Engineer III in our agile team, you will design and deliver reliable data collection, storage, access, and analytics solutions that are secure, stable, and scalable. You will develop, test, and maintain essential data pipelines and architectures, supporting various business functions to achieve the firm’s goals. Working with us, you will use your skills to drive innovation and help shape our team culture. Together, we focus on excellence, collaboration, and continuous improvement.
Job responsibilities:
- Develop workflows and ELT pipelines using Python and Databricks.
- Support review of controls to ensure sufficient protection of enterprise data.
- Implement data security using entitlements frameworks.
- Update logical or physical data models based on new use cases.
- Use SQL frequently and understand NoSQL databases.
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 3 years applied experience.
- Good working knowledge of AWS, Databricks, and Python.
- Experience across the data lifecycle.
- Advanced at SQL, including joins and aggregations.
- Working understanding of NoSQL databases.
- Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns for analysis.
- Utilize AWS Cloud Services for developing, deploying, and managing applications at scale.
- Good understanding and working knowledge of software development lifecycle tools used for configuration management, CI/CD pipelines, unit testing, regression testing, and performance testing.
Preferred qualifications, capabilities, and skills:
- Familiarity with the Standardized data layer practices (Medallion architecture).
- Exposure to Aurora Postgres and MongoDB.
- Skills in designing efficient data models including normalization, denormalization, and schema design and an understanding around relational and star schemas.
Data Engineer II - Python, SQL - Senior Associate in London employer: JPMorganChase
At JPMorgan Chase, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As a Data Engineer II, you will not only have the chance to work with cutting-edge technologies but also enjoy ample opportunities for professional growth within a supportive environment. Our commitment to excellence and continuous improvement ensures that your contributions will make a meaningful impact on our business objectives while working alongside talented professionals in a dynamic team.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer II - Python, SQL - Senior Associate in London
✨Tip Number 1
Network like a pro! Reach out to current employees at JPMorgan Chase on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data engineering projects, especially those involving Python, SQL, and AWS. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Brush up on common data engineering interview questions and scenarios. Mock interviews with friends or mentors can help you articulate your thought process and problem-solving skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team at StudySmarter and contributing to our culture of innovation.
We think you need these skills to ace Data Engineer II - Python, SQL - Senior Associate in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer II role. Highlight your expertise in Python, SQL, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our goals at JPMorgan Chase. Let us know what excites you about this opportunity!
Showcase Your Projects:If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work that demonstrate your skills in developing workflows and ELT pipelines. We love seeing real examples of your capabilities.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Let’s get started on this journey together!
How to prepare for a job interview at JPMorganChase
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, and any relevant tools like Databricks and AWS. Brush up on your knowledge of ELT pipelines and data security practices, as these will likely come up during the interview.
✨Showcase Your Experience
Prepare to discuss specific projects where you've developed data pipelines or worked with NoSQL databases. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your contributions.
✨Understand the Business Impact
Be ready to explain how your work as a Data Engineer can drive business objectives. Think about how your data solutions have improved efficiency or decision-making in past roles, and be prepared to share those insights.
✨Ask Insightful Questions
Prepare thoughtful questions about the team culture, ongoing projects, and how they measure success. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
