Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deliver high-quality data solutions that power AI and generate business value.
- Company: Join Slalom, a forward-thinking consultancy with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on learning and knowledge sharing.
- Why this job: Be at the forefront of AI and data engineering, making a real impact.
- Qualifications: 3-5 years in data engineering, strong Python skills, and cloud platform experience.
The predicted salary is between 60000 - 80000 £ per year.
As a Data Engineer (Consultant) at Slalom, you will design and deliver high-quality data solutions that power AI and generate measurable business value for our clients. You will build pipelines, platforms, and feature stores that feed modern AI and analytics workloads, using AI tooling as a first-class part of your workflow.
Responsibilities
- Client Delivery & Technical Execution
- Build AI-ready data platforms.
- Design and implement the Snowflake data layers, feature stores, and pipelines that feed production AI, machine learning, and agentic workloads.
- Deliver on Snowflake end-to-end: ingestion, transformation, performance tuning, security, and role design, including native integration with Snowflake Cortex for in-platform AI, LLM, and embedding workloads.
- Engineer in Python as a core craft, using it for data processing, orchestration, automation, and integration with AI/ML services and agentic frameworks.
- Implement data architectures on AWS or Azure, with Databricks and Microsoft Fabric experience a strong plus.
- Apply AI-assisted development as the default way of working.
- Collaborate with AI/ML engineers, data scientists, and DevOps teams on integrated solutions.
- Apply platform best practices: security, performance, cost optimisation, and operational excellence across Snowflake and cloud environments.
- Work with architects, analysts, and business stakeholders to turn requirements into implementations.
- Contribute to consulting delivery: planning, estimation, and delivery as part of a project team.
- Client Collaboration & Communication
- Participate in client workshops, requirements-gathering sessions, and solution design discussions.
- Communicate technical concepts clearly to both technical and non-technical audiences.
- Build positive working relationships with client stakeholders through reliable delivery and transparent communication.
- Practice Development & Knowledge Sharing
- Stay current with the Snowflake, Python, and AI engineering ecosystems.
- Contribute to internal accelerators, templates, and reusable components for AI-enabled data engineering.
- Share knowledge through documentation, demos, and informal mentoring of peers.
- Participate actively in Slalom’s learning culture.
Qualifications
- Core Experience
- 3 to 5 years of experience in data engineering, with hands-on work on cloud data platforms.
- Strong practical experience with Snowflake.
- Working knowledge of Snowflake Cortex.
- Strong proficiency in Python and SQL.
- Experience with AWS or Azure data services.
- Experience designing and implementing ETL/ELT pipelines.
- Solid understanding of data modelling concepts.
- AI-native mindset
- Active user of AI-assisted development tools.
- Curiosity about agentic AI and production ML pipelines.
- An understanding of how data engineering decisions shape AI and ML outcomes.
- Good to have
- Experience with Databricks.
- Exposure to Microsoft Fabric.
- Awareness of data governance principles.
- Familiarity with CI/CD and Infrastructure as Code tools.
- Relevant cloud certifications.
How You Work
- Strong problem-solving skills and the ability to work in fast-paced consulting environments.
- Solid communication and interpersonal skills.
- Prior client-facing experience is preferred but not required.
- A strong interest in consulting and working directly with clients is important.
Data Engineer employer: Slalom
Contact Detail:
Slalom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data engineering game. You never know when a casual chat could lead to your next big opportunity!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Snowflake, Python, and cloud platforms. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process clearly, especially how you’d tackle building AI-ready data platforms. Remember, it’s all about demonstrating your problem-solving skills!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Plus, it’s a great way to ensure your application gets the attention it deserves!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your experience with Snowflake, Python, and cloud platforms like AWS or Azure. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our needs. Don’t forget to mention any AI tools you've used – we love that stuff!
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's building data pipelines or using AI in your workflows, we want to see what you've done and how it relates to the role.
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 – just a few clicks and you’re done!
How to prepare for a job interview at Slalom
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Snowflake and Python. Brush up on your knowledge of AWS or Azure services, as well as data modelling concepts. Being able to discuss these confidently will show that you're ready to hit the ground running.
✨Showcase Your AI Mindset
Since an AI-native mindset is crucial for this role, be prepared to discuss how you've used AI-assisted development tools in your previous projects. Share specific examples of how these tools have improved your workflow or project outcomes, demonstrating your proactive approach to integrating AI into data engineering.
✨Communicate Clearly and Effectively
Practice explaining complex technical concepts in simple terms. You might need to communicate with both technical and non-technical stakeholders, so being able to bridge that gap is key. Consider preparing a few scenarios where you successfully communicated technical ideas to diverse audiences.
✨Prepare for Collaborative Scenarios
Expect questions about teamwork and collaboration, especially since this role involves working with AI/ML engineers and data scientists. Think of examples from your past experiences where you’ve successfully partnered with others to deliver a project, highlighting your ability to build positive relationships and contribute to a team.