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For Companies At a Glance
- Tasks: Design and build cloud-based data pipelines using AWS tools for financial transformation.
- Company: Join a leading tech consultancy shaping the future of digital financial services.
- Benefits: Enjoy competitive pay, health insurance, flexible holidays, and continuous learning opportunities.
- Why this job: Make a real impact in the financial sector while working with cutting-edge technology.
- Qualifications: Experience in Python, Scala, or Java, and knowledge of Big Data technologies required.
- Other info: Collaborative culture with a focus on diversity, equity, and inclusion.
The predicted salary is between 48000 - 72000 £ per year.
Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent
Engineer future-ready data platforms that power financial transformation.
The Role
We’re looking for a Principal Data Engineer with AWS to join our growing team of engineering experts driving next-gen transformation for Tier 1 financial services clients. You’ll play a pivotal role in designing, building, and deploying cloud-based data pipelines. Working across greenfield projects and enterprise-scale platforms, your work will directly impact the way data is ingested, transformed, and served at scale across the financial services industry.
What You’ll Do
- Design and build end-to-end data pipelines leveraging AWS-native tools and modern data architectures.
- Collaborate with clients to gather requirements, define solutions, and deliver production-grade systems.
- Apply AWS Well-Architected Principles to ensure scalability, security, and resilience.
- Lead in the development of robust, tested, and fault-tolerant data engineering solutions.
- Support and mentor junior engineers, contributing to knowledge sharing across the team.
What We’re Looking For
- Proficient in one of Python, Scala or Java, with strong experience in Big Data technologies such as: Spark, Hadoop etc.
- Practical knowledge of building real-time event streaming pipelines (e.g., Kafka, Spark Streaming, Kinesis).
- Proficiency in AWS cloud environments.
- Proven experience developing modern data architectures including Data Lakehouse and Data Warehousing.
- A solid understanding of CI/CD practices, DevOps tooling, and data governance including GDPR.
Bonus Points For
- Expertise in Data Modelling, schema design, and handling both structured and semi-structured data.
- Familiarity with distributed systems such as Hadoop, Spark, HDFS, Hive, Databricks.
- Exposure to AWS Lake Formation and automation of ingestion and transformation layers.
- Background in delivering solutions for highly regulated industries.
- Passion for mentoring and enabling data engineering best practices across teams.
Why Join Capco
- Deliver high-impact technology solutions for Tier 1 financial institutions.
- Work in a collaborative, flat, and entrepreneurial consulting culture.
- Access continuous learning, training, and industry certifications.
- Be part of a team shaping the future of digital financial services.
- Help shape the future of digital transformation across FS & Energy.
We offer a competitive, people-first benefits package designed to support every aspect of your life:
- Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
- Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
- Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
- Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
- Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
- Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick—workshops, certifications, e-learning—your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
- Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.
Inclusion at Capco
We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity and inclusivity, and we bring a collaborative mindset to our partnerships with clients and colleagues. #BeYourselfAtWork is the cornerstone of our success and a value that our employees live and breathe every day.
Principal Data Engineer - AWS employer: Capco
Contact Detail:
Capco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Engineer - AWS
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at Capco. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your experiences with AWS, data pipelines, and any cool projects you've worked on. Let them see your passion for data engineering!
✨Prepare for Technical Challenges
Brush up on your coding skills and be ready for technical interviews. Practice common data engineering problems and be prepared to discuss your approach to building scalable systems. We want to see how you think!
✨Apply Through Our Website
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 serious about joining our team at Capco!
We think you need these skills to ace Principal Data Engineer - AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Principal Data Engineer role. Highlight your experience with AWS, data pipelines, and any relevant Big Data technologies. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Don't forget to mention any specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills: Be sure to list your technical skills clearly, especially your proficiency in Python, Scala, or Java, and your experience with AWS tools. We love seeing candidates who can demonstrate their hands-on experience with real-time event streaming and modern data architectures.
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 don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Capco
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS-native tools and Big Data technologies like Spark and Hadoop. Brush up on your Python, Scala, or Java skills, as you'll likely be asked to demonstrate your proficiency during the interview.
✨Showcase Real-World Experience
Prepare to discuss specific projects where you've designed and built data pipelines or worked with real-time event streaming. Use examples that highlight your problem-solving skills and how you applied AWS Well-Architected Principles to ensure scalability and security.
✨Emphasise Collaboration
Since the role involves working closely with clients and mentoring junior engineers, be ready to share experiences that showcase your collaborative spirit. Talk about how you’ve gathered requirements from clients and contributed to team knowledge sharing.
✨Understand Compliance and Governance
Familiarise yourself with data governance practices, especially GDPR, as this is crucial in financial services. Be prepared to discuss how you’ve ensured compliance in past projects and how you approach data modelling and schema design.
