At a Glance
- Tasks: Design and build data pipelines using Snowflake and modern tools like dbt and Fivetran.
- Company: Join a growing tech company with a strong data culture and innovative projects.
- Benefits: Earn up to £75,000, enjoy hybrid work, 25 days leave, health cover, and pension contributions.
- Other info: Collaborate closely with analysts and data scientists in a dynamic environment.
- Why this job: Take ownership of the data platform and influence its technical direction.
- Qualifications: 4+ years in data engineering, strong Snowflake and SQL skills required.
The predicted salary is between 63000 - 77000 £ per year.
A Senior Data Engineer role with Snowflake at the core of the stack, focusing on a modern data stack including Snowflake, dbt, Fivetran, and cloud orchestration. This position offers hybrid working with flexibility and a salary up to £75,000 depending on experience. You will have ownership of the data platform that the business runs its analytics on.
Our client is a growing technology business that has built its analytics and data capability around the modern data stack. Snowflake is their cloud data warehouse of choice, and they have invested in the surrounding tooling, including dbt for transformation, Fivetran for ingestion, and a cloud-native orchestration layer. The data engineering team works closely with analytics, product, and engineering functions, and the expectation is that this hire is a genuine contributor to the technical direction of the platform.
This role involves designing and building the pipelines, data models, and transformation logic that power reporting, analytics, and data product delivery across the business. You will own the quality, reliability, and performance of data flowing through the warehouse, collaborating closely with analysts and data scientists to ensure the data they rely on is well-structured, documented, and consistently delivered. Additionally, you will contribute to platform governance, cost management, and the continued evolution of the data architecture.
Key Responsibilities:- Design, build, and maintain data pipelines and transformation logic in Snowflake and dbt.
- Manage and optimise data ingestion from multiple sources using Fivetran, custom pipelines, or API integrations.
- Develop and own the Snowflake data model, ensuring it is performant, well-documented, and easy to consume.
- Implement data quality checks, testing frameworks, and monitoring across the transformation layer.
- Orchestrate pipeline execution and dependency management using Airflow or equivalent tooling.
- Manage Snowflake cost and performance through warehouse sizing, query optimisation, and resource management.
- Collaborate with analysts and data scientists to understand consumption patterns and design for their needs.
- Contribute to data governance, access controls, and documentation standards.
- Essential: 4+ years of commercial data engineering experience.
- Strong hands-on Snowflake experience including schema design, query optimisation, and warehousing.
- Proficiency with dbt for transformation layer development and testing.
- Experience with data ingestion tooling (Fivetran, Airbyte, Stitch or similar).
- Strong SQL skills and Python for pipeline development.
- Right to work in the UK or Republic of Ireland.
- Nice to have: Snowflake certifications (SnowPro Core or higher).
- Experience with cloud platforms (AWS, Azure or GCP) alongside Snowflake.
- Familiarity with Streamlit for lightweight data application development.
Why Apply? Salary up to £75,000 depending on experience, hybrid working model with flexible arrangements, 25 days annual leave plus bank holidays, health cover and pension contribution, and ownership of the data platform.
Contact Ryan Quinn at Ocho People via LinkedIn or send in your CV via the portal. All enquiries are handled in strict confidence.
Data Engineer ( Snowflake ) employer: Ocho
Join a dynamic and innovative digital consultancy that champions a remote-first work culture, offering exceptional benefits such as a competitive salary, generous annual leave, and a commitment to professional development. With a focus on quality and collaboration, you'll thrive in an environment that values your expertise and provides the autonomy to shape QA processes while working on complex, multi-component systems alongside a talented team in Northern Ireland.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer ( Snowflake )
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We think you need these skills to ace Data Engineer ( Snowflake )
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ocho. 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 Ocho
✨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!
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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
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✨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.
