At a Glance
- Tasks: Build a data lake and develop pipelines for seamless data integration.
- Company: Dynamic tech firm focused on innovative data solutions.
- Benefits: Competitive daily rate, hybrid work model, and opportunities for professional growth.
- Other info: Exciting projects using AI tools and cloud technologies.
- Why this job: Join a cutting-edge team and shape the future of data engineering.
- Qualifications: 2-5 years in data engineering with strong SQL and Python skills.
A hands-on engineer to build out the data lake that will become the single source of truth for the business — so that iPaaS pulls from one governed, canonically-modelled platform rather than integrating directly with five separate systems. Working to the architecture and standards set by the Data Lead, this role delivers the pipelines, models and integrations that make the lake real. Day to day on Microsoft (Azure / Fabric) today, with a likely move to Google Cloud, so portable, vendor-neutral build habits matter.
What Youll Do
- Build the lake: Develop ingestion pipelines and the landing → curated → serving layers, following the platform design and patterns set by the Data Lead.
- Implement the canonical model: Map and transform data from the five source systems into the shared canonical model, so downstream consumers work from one consistent vocabulary.
- Re-point iPaaS: Migrate integrations to source from the lake, building reusable ingestion/publishing flows and helping retire legacy point-to-point connections.
- Data quality reliability: Implement validation, monitoring and alerting; keep pipelines tested, documented and dependable.
- Use AI in the build: Apply AI-assisted tooling — schema mapping, data-quality checks, code and pipeline generation — to work faster, and help prepare clean, well-structured data for AI/ML and analytics consumption.
- Build portably: Use open table formats (Delta / Iceberg), SQL, Python and infrastructure-as-code so the Azure→GCP move is straightforward.
What Youll Bring
- 2–5 years of hands-on data engineering, ideally including work on a data lake or lakehouse.
- Solid SQL and Python, with practical ELT/ETL experience (event streaming, CDC or API-led integration a plus).
- Comfortable building data transformations to a defined model; exposure to canonical / dimensional modelling.
- Hands-on with a cloud data platform — Azure / Fabric and/or GCP (BigQuery, Dataflow); willing to work across both.
- Experience with, or genuine enthusiasm for, AI-assisted engineering tooling.
- Works well to someone elses architecture and standards, asks good questions, and documents as they go.
Senior Engineer, Data Engineering employer: Norton Blake
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact the creation of a centralised data lake. With competitive daily rates and a hybrid working model in London, you'll have access to cutting-edge technology and opportunities for professional growth, all while being part of a team that embraces AI-assisted engineering tools to enhance productivity and data quality.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure or GCP. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data lake projects and any cool pipelines you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your experience with ELT/ETL processes and how you've tackled data quality issues in past projects. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Engineer role. Highlight your hands-on data engineering experience, especially with data lakes and cloud platforms like Azure or GCP.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've built data pipelines or worked with canonical models, and show your enthusiasm for AI-assisted tooling.
Showcase Your Technical Skills:Don’t forget to mention your proficiency in SQL and Python! We want to see your practical ELT/ETL experience, so include any relevant projects or achievements that demonstrate your capabilities.
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 Norton Blake
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals, especially around data lakes and ETL processes. Be ready to discuss your hands-on experience with SQL and Python, as well as any projects where you've built ingestion pipelines or worked with cloud platforms like Azure or GCP.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in previous roles. Whether it's implementing data quality checks or migrating integrations, having a few solid stories that highlight your problem-solving abilities will impress the interviewers.
✨Familiarise Yourself with AI Tools
Since the role involves using AI-assisted tooling, it’s a good idea to get acquainted with the latest AI technologies relevant to data engineering. Be ready to discuss how you've used or would like to use these tools to enhance your workflow and improve data quality.
✨Ask Insightful Questions
Interviews are a two-way street, so come prepared with thoughtful questions about the company's data architecture and standards. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
