Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and build data pipelines to drive business insights and AI solutions.
- Company: Join JPMorgan Chase's innovative Security Services team.
- Benefits: Competitive salary, career growth, and a chance to work with cutting-edge technology.
- Other info: Collaborative culture with opportunities for professional development.
- Why this job: Make a real impact by enabling data-driven decisions in a dynamic environment.
- Qualifications: Experience with Databricks, Python, and strong data modelling skills required.
The predicted salary is between 100000 - 150000 £ per year.
Be part of a team that creates the strategic data assets driving business insight, operational excellence, and the next generation of AI solutions. Your work will directly enable the business to answer key questions, track progress on objectives, and unlock new opportunities through data.
As a Data Engineer in the Security Services Data Modelling and Engineering team, within AI Transformation, you will play a pivotal role in building the data foundation that powers business insights, OKR tracking, and AI enablement across JPMorganChase’s Security Services businesses. You will design and develop scalable data pipelines and reusable datasets on Databricks, collaborating with Data Architects and Business Analysts to deliver high-quality, compliant, and business-driven solutions.
Job Responsibilities- Design, build, and optimize data pipelines and transformation workflows on Databricks, leveraging Python and Spark.
- Collaborate with Data Architects and Business Analysts to develop robust data models and clearly document data flows and ETL logic.
- Implement and execute data quality checks and validation modules using Python.
- Maintain transparency and accountability by tracking work and progress in Jira.
- Ensure datasets and pipelines are accurately registered in relevant catalogues and consoles, meeting governance and privacy standards.
- Proven experience developing data pipelines and solutions on Databricks.
- Strong proficiency in Python, including libraries for data transformation (e.g., pandas).
- Solid understanding of ETL concepts, data modelling, and pipeline design.
- Experience with Spark and cloud data platforms.
- Ability to document data flows and transformation logic to a high standard.
- Familiarity with project management tools such as Jira.
- Collaborative mindset and strong communication skills.
- Experience in financial services or large enterprise data environments.
- Knowledge of data governance, privacy, and compliance requirements.
- Exposure to business analysis and requirements gathering.
Security Services Data Modelling and Engineering - Vice President employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Security Services Data Modelling and Engineering - Vice President
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on 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 data pipelines and projects. This is your chance to demonstrate your expertise in Python, Spark, and Databricks. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with ETL concepts and data modelling. Practice common interview questions and think about how you can relate your past work to the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and take the initiative to reach out directly.
We think you need these skills to ace Security Services Data Modelling and Engineering - Vice President
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with data pipelines, Python, and Databricks. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of projects where you've designed and built data pipelines. We love seeing real-world applications of your skills, especially if they relate to financial services or large data environments.
Be Clear and Concise: When writing your cover letter, get straight to the point. Explain why you're a great fit for the role and how you can contribute to our team. We appreciate clarity and directness!
Apply Through Our Website: Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can't wait to hear from you!
How to prepare for a job interview at J.P. Morgan
✨Know Your Data Inside Out
Make sure you’re well-versed in the data pipeline processes and tools mentioned in the job description, especially Databricks, Python, and Spark. Brush up on your ETL concepts and be ready to discuss how you've implemented these in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working closely with Data Architects and Business Analysts, prepare examples that highlight your teamwork and communication skills. Think of specific instances where you collaborated on a project and how it led to successful outcomes.
✨Demonstrate Your Problem-Solving Abilities
Be ready to tackle hypothetical scenarios or case studies during the interview. They might ask how you would approach building a data pipeline or resolving data quality issues. Use your experience to illustrate your thought process and solutions.
✨Familiarise Yourself with Governance Standards
Understanding data governance and compliance is crucial for this role. Research the relevant standards and be prepared to discuss how you’ve ensured compliance in your previous work. This will show that you take data privacy seriously and can navigate complex regulations.