Data Engineer (Snowflake) – AI/Data Consulting Firm
About Us
We are an ambitious consulting firm focused on delivering cutting-edge solutions in data and AI. Our mission is to empower organisations to unlock the full potential of their data by leveraging platforms like Snowflake alongside other emerging technologies. As a Data Engineer, you will play a crucial role in building and optimising data solutions, ensuring scalability, performance, and reliability for our clients’ complex data challenges.
The Role
As a Data Engineer (Snowflake), you will be responsible for designing, implementing, and optimising large-scale data processing systems. You’ll work closely with clients, data scientists, and solution architects to build efficient data pipelines, reliable infrastructure, and scalable analytics capabilities. This role requires strong technical expertise, problem-solving ability, and the confidence to work in a dynamic, client-facing environment.
Your Impact:
- Develop, implement, and optimise data pipelines and ELT processes on Snowflake.
- Work closely with clients to understand business requirements and translate them into technical solutions.
- Design and implement scalable, high-performance cloud data architectures.
- Ensure data integrity, quality, and security through robust engineering practices.
- Monitor, troubleshoot, and optimise data workflows for efficiency and cost-effectiveness.
- Collaborate with data scientists and analysts to enable analytics and machine learning solutions.
- Contribute to best practices, coding standards, and documentation to improve data engineering processes.
- Mentor junior engineers and support knowledge-sharing across teams.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines using Snowflake, dbt, and SQL.
- Develop efficient ELT workflows to process large volumes of structured and semi-structured data.
- Implement data governance, security, and compliance standards within Snowflake environments.
- Work with cloud platforms such as AWS, Azure, or GCP to manage data storage and integration.
- Collaborate with cross-functional teams to enhance data accessibility and usability.
- Optimise data warehouse architectures for performance, scalability, and cost efficiency.
- Maintain and improve CI/CD processes for data pipeline deployment and monitoring.
What We Are Looking For:
- 5+ years of experience in data engineering or related roles.
- Strong expertise in Snowflake, SQL, and cloud data platforms (AWS, Azure, or GCP).
- Proficiency in Python for data transformation and automation.
- Experience with ELT development and orchestration tools (e.g. dbt, Airflow, Prefect).
- Knowledge of data modelling, data warehousing, and modern analytics architectures.
- Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code.
- Strong problem-solving skills and the ability to work in fast-paced environments.
- Excellent communication and stakeholder management skills.
Preferred Qualifications:
- Experience integrating Snowflake with data visualisation or ML platforms.
- Knowledge of data streaming technologies such as Kafka or Kinesis.
- Familiarity with Terraform or similar infrastructure automation tools.
- Previous experience in consulting or client-facing delivery roles.
What We Offer:
- Competitive compensation, including performance-based incentives.
- Opportunities for professional growth and development in a fast-growing firm.
- A collaborative and supportive environment that values innovation, excellence, and client success.
If you’re passionate about data engineering and ready to make an impact in AI-driven consulting, we’d love to hear from you!
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Snowflake) in Edinburgh
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Ethiq!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Ethiq.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer (Snowflake) at Ethiq, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Ethiq, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ethiq. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ethiq
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ethiq!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
