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- Tasks: Lead the design and development of scalable data solutions in a modern data environment.
- Company: Join a forward-thinking company investing in cutting-edge technology.
- Benefits: Competitive pay, remote work options, and opportunities for professional growth.
- Other info: Exciting opportunity to elevate engineering 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 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
✨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 lookout for opportunities. You never know who might have a lead or can refer you to a role that fits your skills.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Snowflake, dbt, and Python. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and best practices in data engineering. Be ready to discuss how you've implemented CI/CD pipelines and DataOps principles in past roles — this is your chance to shine!
✨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 the initiative to connect directly with us.
We think you need these skills to ace Lead data analytics engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Lead Analytics Engineer role. Highlight your expertise with Snowflake, dbt, Python, and AWS, as well as any experience with CI/CD and DataOps practices.
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 raised engineering standards or implemented best practices in previous positions. Show us your passion for building modern data platforms!
Showcase Your Technical Leadership: Since this is a technical leadership role, make sure to emphasise your experience in leading by example. Talk about how you've influenced architecture and standards in past projects, and how you can bring that expertise to our team.
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 out on any important updates regarding your application status.
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 Snowflake, dbt, Python, and AWS. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects. This will show that you’re not just familiar with the tools but can also leverage them effectively.
✨Showcase Your DataOps Experience
Be prepared to talk about your experience with CI/CD pipelines and DataOps practices. Share specific examples of how you've implemented these principles in previous roles, especially if you’ve used GitHub Actions or similar tools. This will demonstrate your ability to drive modern engineering standards.
✨Communicate Clearly and Confidently
Since this role requires excellent communication skills, practice articulating your thoughts clearly. Think about how you can inspire confidence in your technical abilities and leadership style. Use examples from your experience to illustrate your points and engage your interviewers.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in a data environment. Prepare for scenarios where you might need to design a data pipeline or improve data quality. Think through your approach and be ready to explain your reasoning, as this will highlight your technical leadership capabilities.