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- Tasks: Lead the design and development of scalable data solutions in a modern environment.
- Company: Join a forward-thinking company investing in cutting-edge data technology.
- Benefits: Flexible remote work, competitive pay, and opportunities for professional growth.
- Other info: Exciting opportunity to elevate technical standards in a dynamic, growing team.
- Why this job: Shape the future of data engineering and influence best practices from the ground up.
- Qualifications: Proven experience in data engineering with expertise in Snowflake, dbt, Python, and AWS.
The predicted salary is between 70000 - 90000 £ per year.
We’re looking for a Lead Analytics Engineer to join a major CRM migration programme and help shape the future of a growing modern data function. This is not a people management role — we need a true technical leader. Someone who can come in, raise engineering standards, implement best practices, and show the existing team what “good” looks like in a modern data environment.
You’ll be joining at a genuinely exciting stage: the business is investing heavily in new technology and modernizing its data platform from the ground up. Rather than inheriting years of technical debt, you’ll have the opportunity to influence architecture, standards, and ways of working from the beginning.
Tech Stack:
- Snowflake
- dbt
- Python
- AWS
- Power BI
Responsibilities:
- Designing, developing, and evolving scalable Data Warehouse and ELT solutions
- Driving modern DataOps practices including CI/CD, GitOps, testing, and automation
- Implementing robust, observable, and high-quality data pipelines
- Leading by example within engineering teams and elevating technical standards
- Supporting the move toward cross-functional product squads
- Working closely with governance and analytics teams to build mature, scalable solutions
What we’re looking for:
- Proven Lead-level Data/Analytics Engineering experience
- Strong expertise with Snowflake, dbt, Python, and AWS
- Deep understanding of software engineering best practices within data environments
- Experience implementing CI/CD pipelines and DataOps principles (GitHub Actions etc.)
- Strong experience with Data Observability and Data Quality frameworks
- Excellent communication skills and the ability to inspire confidence across teams
- Experience working in modern, mature data environments
Nice to Have:
- Exposure to data products
- Experience with data cataloguing/discovery tools
- Strong Agile and continuous improvement mindset
This is an ideal opportunity for someone who enjoys building modern data platforms the right way — influencing engineering culture, tooling, and delivery standards at a critical stage of growth. If interested, drop me a message or apply directly.
Lead data analytics engineer in London employer: SR2 | Socially Responsible Recruitment | Certified B Corporation™
Contact Detail:
SR2 | Socially Responsible Recruitment | Certified B Corporation™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead data analytics engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data analytics field and let them know you're on the hunt for a Lead Analytics Engineer role. You never know who might have the inside scoop on an opportunity or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving Snowflake, dbt, and Python. This will give potential employers a taste of what you can bring to the table and how you can elevate their engineering standards.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and best practices in DataOps. Be ready to discuss how you've implemented CI/CD pipelines and improved data quality in past roles. Confidence in your expertise can really set you apart!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Lead data analytics engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead Analytics Engineer. Highlight your experience with Snowflake, dbt, Python, and AWS, and don’t forget to showcase your understanding of DataOps practices. We want to see how you can elevate engineering standards!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of how you've influenced architecture and standards in previous roles. We love seeing passion and clarity in your writing!
Showcase Your Technical Skills: In your application, make sure to highlight your technical expertise. Discuss your experience with CI/CD pipelines and data observability frameworks. We’re looking for someone who can lead by example, so let us know how you’ve done that in the past!
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 any important updates. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B Corporation™
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Snowflake, dbt, Python, and AWS. Brush up on your knowledge of DataOps practices and be ready to discuss how you've implemented CI/CD pipelines in past projects.
✨Showcase Your Leadership Skills
Even though this isn’t a people management role, it’s crucial to demonstrate your ability to lead by example. Prepare examples of how you've raised engineering standards or influenced teams in previous roles. Highlight your experience in modern data environments and how you can inspire confidence across teams.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and understanding of data engineering best practices. Be ready to discuss how you would design scalable data solutions and implement robust data pipelines. Practising common interview questions can help you articulate your thought process clearly.
✨Communicate Your Vision
This role is about shaping the future of a growing data function, so be prepared to share your vision for modernising data platforms. Discuss how you would approach architecture and standards, and be ready to explain your strategies for building mature, scalable solutions that align with the company’s goals.