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For Companies At a Glance
- Tasks: Lead the migration of legacy data workflows to high-performance AWS cloud using PySpark.
- Company: Join a dynamic team in the financial services sector, fully remote.
- Benefits: Enjoy 33 days holiday and flexible working arrangements.
- Why this job: Make a significant impact on data modernisation in a cutting-edge environment.
- Qualifications: 5+ years of PySpark experience and strong AWS skills required.
- Other info: Collaborate with a talented team and enhance your technical expertise.
The predicted salary is between 54000 - 84000 £ per year.
We are seeking a Lead PySpark Engineer to drive a large-scale data modernisation project, transitioning legacy data workflows into a high-performance AWS cloud environment. This is a hands-on technical role focused on converting legacy SAS code into production-ready PySpark pipelines within a complex financial services landscape.
Key Responsibilities
- Code Conversion: Lead the end-to-end migration of SAS code (Base SAS, Macros, DI Studio) to PySpark using automated tools (SAS2PY) and manual refactoring.
- Pipeline Engineering: Design, build, and troubleshoot complex ETL/ELT workflows and data marts on AWS.
- Performance Tuning: Optimise Spark workloads for execution efficiency, partitioning, and cost-effectiveness.
- Quality Assurance: Implement clean coding principles, modular design, and robust unit/comparative testing to ensure data accuracy throughout the migration.
- Engineering Excellence: Maintain Git-based workflows, CI/CD integration, and comprehensive technical documentation.
Technical Requirements
- PySpark (P3): 5+ years of hands-on experience writing scalable, production-grade PySpark/Spark SQL.
- AWS Data Stack (P3): Strong proficiency in EMR, Glue, S3, Athena, and Glue Workflows.
- SAS Knowledge (P1): Solid foundation in SAS to enable the understanding and debugging of legacy logic for conversion.
- Data Modeling: Expertise in ETL/ELT, dimensions, facts, SCDs, and data mart architecture.
- Engineering Quality: Experience with parameterisation, exception handling, and modular Python design.
Additional Details
- Industry: Financial Services experience is highly desirable.
- Working Pattern: Fully remote with internal team collaboration days.
- Benefits: 33 days holiday entitlement (pro-rata).
PySpark Developer in Slough employer: Randstad Digital
Contact Detail:
Randstad Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PySpark Developer in Slough
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work with PySpark or in financial services. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your PySpark projects, especially any cloud migration work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common PySpark and AWS questions. Practice explaining your past projects and how you tackled challenges, especially around code conversion and performance tuning.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace PySpark Developer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PySpark and AWS. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Lead PySpark Engineer role. We love seeing your personality and passion for data migration, so let that enthusiasm come through.
Showcase Your Technical Skills: When filling out your application, make sure to detail your hands-on experience with PySpark and AWS services. We’re looking for someone who can hit the ground running, so highlight any relevant tools and technologies you’ve worked with.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Randstad Digital
✨Know Your PySpark Inside Out
Make sure you brush up on your PySpark skills before the interview. Be ready to discuss your experience with writing scalable, production-grade PySpark code and be prepared to explain how you've optimised Spark workloads in the past.
✨Showcase Your AWS Expertise
Since this role involves working with AWS services like EMR, Glue, and S3, it’s crucial to highlight your experience with these tools. Prepare examples of how you've designed and built ETL/ELT workflows in a cloud environment.
✨Understand the Legacy Code
Familiarise yourself with SAS and its functionalities, as you'll need to convert legacy SAS code into PySpark. Being able to discuss your understanding of SAS will show that you can handle the complexities of the migration process.
✨Emphasise Engineering Excellence
Talk about your experience with clean coding principles, modular design, and testing. Highlight any experience you have with Git-based workflows and CI/CD integration, as these are key to maintaining quality in your work.
