At a Glance
- Tasks: Design and optimise scalable data pipelines using Python and AWS services.
- Company: Leading IT solutions provider in the UK and EU market.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative Agile environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team shaping next-gen data platforms and make a real impact.
- Qualifications: Strong Python skills and experience with data engineering fundamentals.
The predicted salary is between 80000 - 100000 £ per year.
We provide end-to-end IT solutions and services including Applications services, Data & Analytics services, AI/ML Technologies and Professional services in the UK and EU market.
Role Overview
We are developing a next-generation data platform and are looking for an experienced Senior Data Engineer to help shape its architecture, reliability, and scalability. The ideal candidate will have more than 10 years of hands-on engineering experience and a strong background in building modern data pipelines, working with cloud-native technologies, and applying robust software engineering practices.
Key Responsibilities
- Design, develop, and optimise scalable, testable data pipelines using Python and Apache Spark.
- Implement batch workflows and ETL processes adhering to modern engineering standards.
- Develop Cloud-Based Workflows
- Orchestrate data workflows using AWS services such as Glue, EMR Serverless, Lambda, and S3.
- Contribute to the evolution of lakehouse architecture leveraging Apache Iceberg.
- Apply Software Engineering Best Practices
- Use version control, CI/CD pipelines, automated testing, and modular code principles.
- Participate in pair programming, code reviews, and architectural design sessions.
- Data Quality & Observability
- Build monitoring and observability into data flows.
- Implement basic data quality checks and contribute to continuous improvements.
- Stakeholder Collaboration
- Work closely with business teams to translate requirements into data-driven solutions.
- Develop an understanding of financial indices and share domain insights with the team.
What You’ll Bring
Technical Expertise
- Strong experience writing clean, maintainable Python code, ideally using type hints, linters, and test frameworks such as pytest.
- Solid understanding of data engineering fundamentals including batch processing, schema evolution, and ETL pipeline development.
- Experience with—or strong interest in learning—Apache Spark for large-scale data processing.
- Familiarity with AWS data ecosystem tools such as S3, Glue, Lambda, and EMR.
Ways of Working
- Comfortable working in Agile environments and contributing to collaborative team processes.
- Ability to engage with business stakeholders and understand the broader context behind technical requirements.
Nice-to-Have Skills
- Experience with Apache Iceberg or similar table formats (e.g., Delta Lake, Hudi).
- Familiarity with CI/CD platforms such as GitLab CI, Jenkins, or GitHub Actions.
- Exposure to data quality frameworks such as Great Expectations or Deequ.
- Interest or background in financial markets, index data, or investment analytics.
AWS Data Engineer in London employer: Technopride Ltd
As an AWS Architect at our London-based company, you will thrive in a dynamic and flexible work environment that champions innovation and collaboration. We offer competitive benefits, a strong focus on employee growth through continuous learning opportunities, and a culture that values diversity and teamwork. Join us to be part of a forward-thinking team dedicated to building cutting-edge cloud solutions while enjoying the perks of hybrid working.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer in London
✨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 in data engineering. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of your projects, especially those involving Python, Apache Spark, or AWS tools. Having tangible examples of your work can really set you apart from the competition.
✨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 your past projects in detail. Confidence is key!
✨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 proactive about their job search.
We think you need these skills to ace AWS Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AWS Data Engineer role. Highlight your experience with Python, Apache Spark, and AWS tools. We want to see how your skills match 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 next-gen data platform. Keep it engaging and relevant to the job description.
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! Whether it's building data pipelines or using cloud-native technologies, we love seeing real-world examples of your work.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Don’t miss out!
How to prepare for a job interview at Technopride Ltd
✨Know Your Tech Inside Out
Make sure you brush up on your Python and Apache Spark skills. Be ready to discuss how you've built data pipelines in the past, and don’t shy away from sharing specific examples of your work with AWS services like Glue and Lambda.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical challenges during the interview. Think about how you would approach designing scalable data workflows or optimising ETL processes. Practising common data engineering problems can really help you shine.
✨Understand the Business Context
Get familiar with financial indices and how they relate to data engineering. Being able to connect your technical skills to business outcomes will impress the interviewers and show that you can translate requirements into actionable solutions.
✨Emphasise Collaboration and Agile Experience
Since the role involves working closely with teams, be prepared to discuss your experience in Agile environments. Share examples of how you've contributed to team processes, participated in code reviews, or engaged with stakeholders to ensure everyone is on the same page.
