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- Tasks: Build and maintain a cutting-edge data platform for financial services.
- Company: Join a forward-thinking company transforming client investment experiences.
- Benefits: Competitive salary, learning opportunities, and a collaborative culture.
- Why this job: Make a real impact in the financial sector while working with talented professionals.
- Qualifications: 8+ years in IT, strong Snowflake and Python skills required.
- Other info: Dynamic role with excellent growth potential in a supportive environment.
The predicted salary is between 70000 - 90000 £ per year.
A key role in helping build the future of financial services, working together with business partners to create client experiences that are changing the way people invest. You will work with smart, talented people across our business. We will expect you to be agile and to think outside the box. In return, we will give you challenging work that makes an impact and brings opportunities to learn and grow, and a collaborative culture that encourages every member of our team to bring their point of view to the table—because that is how we help our clients succeed.
You will be an individual contributor on the Analytics and Data Platform engineering team responsible for architecting, building, testing, and maintaining the data platform. You will be responsible for:
- Contributing to the platform’s architectural design
- Development and testing of the integration, modelling, data persistence and querying tools and analytical systems
- Data pipeline implementation, maintenance and testing
- Metadata management processes and tools
- Monitoring the overall performance and stability of the pipelines
- Implementing data curation, metadata management and data quality tooling
- Engaging with our business and technology partners to ensure that the platform fully meets the firm’s needs
Primary Technical experience/skills
- 8+ years of IT experience
- Snowflake Data Engineer with Python
- Strong understanding of AWS ecosystems like Lambdas, step functions, and ECS services
- Practical experience with Snowflake is required
- Advanced SQL skills
- Experience building modern enterprise-wide data and analytics systems in a financial services organization with an understanding of the asset management business and/or financial markets
Nice to Have:
- Experience with data stack technologies, such as Apache Iceberg & Spark
- Exposure to Apache Airflow, Prefect, Dagster, DBT
- Expertise in data analysis with exposure to data services (such as Glue, Lake Formation, EMR, EventBridge, Athena, etc.) & metadata management tools (such as Amundsen, Atlas, DataHub, OpenDataDiscovery, Marquez, etc.)
- Experience on RDBMS like PostgreSQL would be a plus
Senior Data Engineer in London employer: Hexaware Technologies
Contact Detail:
Hexaware Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that Senior Data Engineer role.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Make sure you can confidently discuss your experience with Snowflake, Python, and AWS. We want you to shine when it comes to showcasing your expertise!
✨Tip Number 3
Don’t just apply anywhere—focus on companies that align with your values and career goals. Check out our website for roles that excite you and fit your skill set. We’re all about finding the right match!
✨Tip Number 4
Follow up after interviews! A quick thank-you email can keep you top of mind and show your enthusiasm for the role. Plus, it’s a great chance to reiterate why you’d be a perfect fit for the team.
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your experience with Snowflake, Python, and AWS ecosystems, as these are key to what we're looking for.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about financial services and how your background makes you a great fit. Don't forget to mention any relevant projects or achievements that showcase your data engineering skills!
Showcase Your Technical Skills: In your application, be specific about your technical expertise. Mention your advanced SQL skills and any experience with data stack technologies like Apache Iceberg or Spark. We want to see how you can contribute to our data platform!
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 Hexaware Technologies
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially with Snowflake and Python. Be ready to discuss your experience with AWS services like Lambdas and ECS. They’ll likely ask you to solve a problem or explain a project you've worked on, so have specific examples at the ready.
✨Understand the Business Context
Since this role is in financial services, it’s crucial to understand how data impacts investment strategies. Familiarise yourself with the asset management business and current trends in financial markets. This will help you connect your technical skills to real-world applications during the interview.
✨Show Your Collaborative Spirit
This company values teamwork, so be prepared to discuss how you’ve worked with others in past projects. Share examples of how you’ve engaged with business partners to meet their needs and how you’ve contributed to a collaborative culture. Highlighting your ability to think outside the box will also score you points!
✨Prepare Questions That Matter
Interviews are a two-way street, so come armed with thoughtful questions about the team, the data platform, and the challenges they face. This shows your genuine interest in the role and helps you assess if it’s the right fit for you. Ask about their approach to data quality and how they measure success in their projects.