At a Glance
- Tasks: Lead the development of data solutions using Snowflake and drive real business value.
- Company: Join Aviva, a leader in innovative insurance technology.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a dynamic team within Aviva Quantum, driving innovation in data science.
- Why this job: Shape the future of insurance with cutting-edge data analytics and technology.
- Qualifications: Proven experience in data engineering and strong knowledge of DataOps and CI/CD.
The predicted salary is between 70000 - 90000 £ per year.
Do you like working with the latest technology and are interested in enhancing your tech abilities? We have an exciting opportunity for a highly skilled Data Engineer with significant experience of Snowflake. As well as being an expert in the Snowflake cloud platform, you’ll have a strong background in Data Ingestion and Integration, designing and implementing data pipelines on various technologies, Data Modelling and a rounded understanding of data warehousing.
Aviva believes strongly in experimentation leading to industrialisation and we are searching for passionate, energetic data engineers who are focussed on using their skills to drive out real business value for our customers.
A bit about the job: An exciting opportunity within one of our Data Engineering teams for a highly skilled individual to work within our data environment, which is helping to shape the future of insurance through cutting-edge predictive analytics and Data Science. Data is the life blood of any modern organisation and Aviva is no different. Our Data Engineering team sits within Aviva Quantum our global Data Science Practise (covering areas including Machine Learning, Analytics, Data Engineering, AI and many more). You will form a vital part of our business, contribute to our first-class end-to-end solutions. You will play an active role in defining our practices, standards and ways of working, and apply them to your role. Be open to working across organisation and team boundaries to ensure we bring the best to our customers.
Skills and experience we’re looking for:
- Experienced data engineering leader delivering data solutions with a strong working knowledge of DataOps and CI/CD best practices
- Experience of building/developing/managing data using Snowflake
Lead Data Engineer in Norfolk employer: Women in Data®
Aviva is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Lead Data Engineer to thrive. With a strong emphasis on employee growth, Aviva offers opportunities to work with cutting-edge technology in a dynamic environment, where your contributions directly impact the future of insurance through advanced data solutions. Located within a global Data Science Practice, you will be part of a passionate team dedicated to driving real business value, while enjoying a supportive atmosphere that encourages experimentation and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer in Norfolk
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Snowflake. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This is your chance to demonstrate your expertise in Data Ingestion, Integration, and Data Modelling to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on DataOps and CI/CD best practices. Be ready to discuss how you've applied these in your previous roles, as this will show you're the right fit for the team at Aviva.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our innovative Data Engineering team.
We think you need these skills to ace Lead Data Engineer in Norfolk
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with Snowflake and any other relevant technologies in your application. We want to see how your skills align with what we're looking for, so don’t hold back!
Tailor Your Application:Take a moment to customise your CV and cover letter for the Lead Data Engineer role. Mention specific projects or experiences that demonstrate your expertise in data ingestion, integration, and modelling. It helps us see you as a perfect fit!
Be Passionate:Let your enthusiasm for data engineering shine through in your application. We love candidates who are excited about using their skills to drive real business value, so share your passion for technology and innovation!
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’s super easy!
How to prepare for a job interview at Women in Data®
✨Know Your Snowflake Inside Out
Make sure you brush up on your Snowflake knowledge before the interview. Be ready to discuss your experience with the platform, including any specific projects you've worked on. Highlight how you've used Snowflake to solve real business problems and drive value.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience in designing and implementing data pipelines. Bring examples of how you've integrated various technologies and the challenges you faced. This will demonstrate your hands-on experience and problem-solving abilities.
✨Understand DataOps and CI/CD Practices
Since the role requires a strong working knowledge of DataOps and CI/CD, be ready to explain these concepts clearly. Share any relevant experiences where you've applied these practices to improve data delivery and quality.
✨Be Ready to Collaborate
Aviva values teamwork across boundaries, so think of examples where you've successfully collaborated with different teams. Discuss how you’ve contributed to defining practices and standards, and how you can bring that collaborative spirit to their Data Engineering team.
