Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and optimise PySpark data pipelines for financial data analysis.
- Company: Join a leading finance firm focused on innovative data solutions.
- Benefits: Enjoy flexible working options and a dynamic team environment.
- Why this job: Make an impact in finance while honing your tech skills in a fast-paced setting.
- Qualifications: Experience in PySpark, Python, and financial markets is essential.
- Other info: Full-time role with opportunities for growth and learning.
The predicted salary is between 72000 - 108000 £ per year.
Seeking a number of Pyspark Developers with experience in big data processing, Python and Apache Spark particularly within the finance domain. Candidates should have experience working with financial instruments, market risk and large scale distributed computing systems. This role involves developing and optimizing data pipelines for risk calculations, trade analytics and regulatory reporting.
Key responsibilities:
- Develop and optimize scalable PySpark-based data pipelines for processing and analyzing large scale financial data.
- Design and implement distributed computing solutions for risk modeling, pricing and regulatory compliance.
- Ensure efficient data storage and retrieval using Big Data.
- Implement best practices for Spark performance tuning including partitioning, caching and memory management.
- Maintain high code quality through testing, CI/CD pipelines and version control (Git, Jenkins).
- Work on batch processing frameworks for Market risk analytics.
Qualifications and Skills:
- Experience in PySpark and Big Data frameworks.
- Proficiency in Python and PySpark with knowledge of core Spark concepts (RDDs, DataFrames, Spark Streaming, etc).
- Experience working in financial markets, risk management and financial instruments.
- Familiarity with market risk concepts including VaR, Greeks, scenario analysis and stress testing.
- Hands-on experience with Hadoop and Spark.
- Proficiency in Git, Jenkins and CI/CD pipelines.
- Excellent problem-solving skills and strong mathematical and analytical mindset.
- Ability to work in a fast-paced financial environment.
Data Analytics Lead (PySpark) - VP employer: Citigroup, Inc.
Contact Detail:
Citigroup, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Lead (PySpark) - VP
✨Tip Number 1
Network with professionals in the finance and data analytics sectors. Attend industry meetups or webinars where you can connect with people who work at StudySmarter or similar companies. This can give you insights into the company culture and potentially lead to referrals.
✨Tip Number 2
Familiarise yourself with the latest trends in big data processing and financial analytics. Follow relevant blogs, podcasts, or online courses that focus on PySpark and its applications in finance. This knowledge will not only help you in interviews but also demonstrate your passion for the field.
✨Tip Number 3
Prepare for technical interviews by practising coding challenges specifically related to PySpark and big data frameworks. Use platforms like LeetCode or HackerRank to sharpen your skills, focusing on problems that involve data manipulation and performance tuning.
✨Tip Number 4
Showcase your experience with financial instruments and risk management in your discussions. Be ready to share specific examples of projects you've worked on that involved market risk analytics or regulatory compliance, as this will highlight your relevance to the role.
We think you need these skills to ace Data Analytics Lead (PySpark) - VP
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark, big data frameworks, and financial markets. Use specific examples that demonstrate your skills in developing data pipelines and working with financial instruments.
Craft a Strong Cover Letter: In your cover letter, explain why you are a great fit for the Data Analytics Lead role. Mention your proficiency in Python and your experience with risk management concepts like VaR and scenario analysis. Show enthusiasm for the finance domain.
Showcase Relevant Projects: If you have worked on projects involving Apache Spark or large-scale distributed computing systems, be sure to include these in your application. Describe your role, the technologies used, and the impact of your work on the project outcomes.
Highlight Problem-Solving Skills: Given the emphasis on problem-solving in the job description, provide examples of challenges you've faced in previous roles and how you overcame them. This could include performance tuning in Spark or optimising data retrieval processes.
How to prepare for a job interview at Citigroup, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with PySpark and big data frameworks in detail. Highlight specific projects where you've developed and optimised data pipelines, especially in the finance domain, as this will demonstrate your relevant expertise.
✨Understand Financial Concepts
Familiarise yourself with key financial concepts such as market risk, VaR, and stress testing. Being able to speak knowledgeably about these topics will show that you understand the context in which your technical skills will be applied.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss how you've tackled complex problems in previous roles. Use examples that showcase your analytical mindset and ability to work under pressure, particularly in fast-paced environments like finance.
✨Emphasise Collaboration and CI/CD Experience
Since the role involves maintaining high code quality through CI/CD pipelines, be ready to talk about your experience with Git, Jenkins, and any collaborative projects. This will highlight your ability to work effectively within a team and maintain code integrity.
