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, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on code quality and continuous learning.
- Why this job: Make a real-world impact by powering trusted financial indices.
- Qualifications: Experience in Python, data engineering, and AWS tools is preferred.
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
Equal Opportunities Statement
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 employer: LSEG
At FTSE Russell, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Lead AWS Software Data Engineer, you'll not only have the opportunity to work with cutting-edge technologies in a modern AWS environment but also benefit from a strong emphasis on professional growth and continuous learning. Our commitment to code quality and teamwork ensures that you will be part of a passionate team dedicated to making a real-world impact in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AWS Software Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at FTSE Russell on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Lead AWS Software Data Engineer role.
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python and AWS skills. Practice coding challenges and be ready to discuss your past projects, especially those involving data pipelines and AWS tools.
✨Tip Number 3
Show your passion for data engineering! During interviews, share your excitement about building scalable systems and how you stay updated with the latest trends in data technology. It’ll make you stand out!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at FTSE Russell.
We think you need these skills to ace Lead AWS Software Data Engineer
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 mention any experiences where you’ve worked closely with product or business teams. Let us know how you’ve translated requirements into data-driven solutions in the past!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
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 around writing clean and maintainable code. Being able to discuss your experience with these technologies will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've designed and developed data pipelines or solved complex data problems in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to see your thought process and impact.
✨Emphasise Collaboration
Since this role involves working closely with product and business teams, be ready to talk about your experiences in Agile environments. Highlight instances where you’ve collaborated effectively, participated in code reviews, or engaged in pair programming. This will demonstrate that you value teamwork and communication.
✨Stay Curious About the Domain
Show your enthusiasm for the financial indices domain by discussing any relevant knowledge or insights you have. If you’ve done any research or have a personal interest in financial markets, bring that up! It’ll show that you’re not just interested in the tech side but also in how it impacts the business.
