At a Glance
- Tasks: Design and develop scalable data pipelines using Python and AWS tools.
- Company: Join FTSE Russell, a leader in financial data solutions.
- Benefits: Competitive salary, inclusive culture, and opportunities for growth.
- Other info: Collaborative environment with a focus on continuous learning.
- Why this job: Make a real-world impact by powering trusted financial indices.
- Qualifications: Experience in Python, AWS, and data engineering basics.
The predicted salary is between 70000 - 90000 € per year.
Ready to build scalable data systems with real-world impact? Join us at FTSE Russell! We’re establishing a team of engineers passionate about data, software craftsmanship, and substantial impact. As a Lead Software Data Engineer, you’ll help power the indices trusted by financial institutions worldwide. You’ll work in a modern AWS environment, build robust pipelines, and collaborate closely with product and business teams to deliver reliable, high-quality data solutions. We care about code quality, ownership, and helping each other grow. If you’re excited about building systems that matter, we’d love to meet you!
WHAT YOU'LL BE DOING
- Designing and developing scalable, testable data pipelines using Python and Apache Spark
- Orchestrating data workflows with AWS tools like Glue, EMR Serverless, Lambda, and S3
- Applying modern software engineering practices: version control, CI/CD, modular design, and automated testing
- Contributing to the development of a lakehouse architecture using Apache Iceberg
- Collaborating with business teams to translate requirements into data-driven solutions
- Building observability into data flows and implementing basic quality checks
- Participating in code reviews, pair programming, and architecture discussions
- Continuously learning about the financial indices domain and sharing insights with the team
WHAT YOU'LL BRING
- Writes clean, maintainable, testable, extensible Python code (ideally with type hints, linters, and tests like pytest)
- Understands data engineering basics: batch processing, schema evolution, and building ETL pipelines
- Has experience with or is eager to learn Apache Spark for large-scale data processing
- Is familiar with the AWS data stack (e.g. S3, Glue, Lambda, EMR)
- Strong experience in relational databases (e.g. Aurora PostgreSQL)
- Enjoys learning the business context and working closely with stakeholders
- Works well in Agile teams and values collaboration over solo heroics
NICE TO HAVES
- Experience with Apache Iceberg or similar table formats
- Familiarity with CI/CD tools like GitLab CI, Jenkins, or GitHub Actions
- Exposure to data quality frameworks like Great Expectations or Deequ
- Experience with other data platforms like Databricks, etc.
- Curiosity about financial markets, index data, or investment analytics
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Lead AWS Software Data Engineer in London employer: LSEG
At FTSE Russell, we pride ourselves on being an exceptional employer, fostering a collaborative and innovative work culture that empowers our employees to thrive. As a Lead AWS Software Data Engineer, you'll not only contribute to impactful data solutions but also benefit from continuous learning opportunities and a supportive environment that values code quality and teamwork. Located in a dynamic industry, we offer the chance to work with cutting-edge technologies while making a real difference in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AWS Software Data Engineer in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at FTSE Russell. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving AWS, Python, and data pipelines. This will give us a clear picture of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding data engineering concepts. Practice common interview questions and be ready to discuss how you've tackled challenges in past projects.
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Lead AWS Software Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead AWS Software Data Engineer role. Highlight your experience with Python, AWS tools, and data engineering practices to show us you’re the perfect fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about building scalable data systems. Share specific examples of your past projects and how they relate to the work we do at FTSE Russell.
Showcase Your Collaboration Skills:We value teamwork, so don’t forget to mention your experience working in Agile teams. Talk about how you’ve collaborated with business teams or contributed to code reviews to demonstrate your commitment to growth and quality.
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 shows us you’re keen on joining our team!
How to prepare for a job interview at LSEG
✨Know Your Tech Stack
Make sure you’re well-versed in the AWS tools mentioned in the job description, like Glue, Lambda, and EMR. Brush up on your Python skills, especially with type hints and testing frameworks like pytest, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've designed and developed scalable data pipelines or tackled challenges in previous projects. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand the Business Context
Familiarise yourself with financial indices and how they impact institutions. Being able to translate business requirements into data-driven solutions will show that you’re not just a techie but also understand the bigger picture.
✨Emphasise Collaboration
Since the role involves working closely with product and business teams, be ready to discuss your experience in Agile environments. Share examples of how you’ve collaborated with others, participated in code reviews, or engaged in pair programming to demonstrate your team spirit.
