At a Glance
- Tasks: Build and optimise data pipelines on Snowflake for impactful analytics and reporting.
- Company: Join Gigaclear, a pioneering Fibre Broadband company transforming connectivity in the UK.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a dynamic team focused on innovation and continuous improvement.
- Why this job: Make a real difference by enabling data-driven insights in a rapidly evolving tech landscape.
- Qualifications: Experience with cloud-based data solutions, SQL, Python, and Snowflake is essential.
The predicted salary is between 60000 - 80000 £ per year.
As a Senior Data Engineer within the Data Engineering team, you will play a key role in building, enhancing, and maintaining our enterprise data platform on Snowflake. You will develop and optimise scalable data pipelines and models that bring data from core business systems into Snowflake, enabling analytics, reporting, and data-driven insights across the organisation. You will translate the data platform strategy into high-quality technical solutions, ensuring our Snowflake environment is reliable, well-structured, and performant. You will champion engineering best practices and contribute to standards that improve the quality, consistency, and usability of data assets. Your work will ensure the business has access to trusted, timely, and well-modelled data to support decision-making, operational reporting, and the foundations for advanced analytics and future AI/ML capabilities.
Key Accountabilities & Responsibilities
- Snowflake Data Engineering Delivery: Design, build, and maintain high-quality data pipelines and models in Snowflake to support business analytics, BI, and operational reporting needs.
- Data Architecture Implementation: Translate the defined data architecture and standards into implemented solutions—including ingestion, transformation, storage, and performance optimisation.
- Pipeline Development & Orchestration: Develop robust ELT/ETL pipelines using dbt and workflow/orchestration tools (e.g., Argo Workflows), ensuring reliability, maintainability, and adherence to engineering best practices.
- Performance & Cost Optimisation: Implement Snowflake warehouse configurations and query optimisation techniques to ensure efficient usage and predictable cost.
- Data Quality & Governance Execution: Apply data quality checks, lineage tracking, and security standards across the data estate. Ensure compliance with data policies, InfoSec controls, and regulatory requirements as required.
- Tooling & Feature Adoption: Leverage Snowflake capabilities (Tasks, Streams, Snowpark, Time Travel, Secure Data Sharing) to improve automation, reduce manual effort, and enhance data accessibility across the business.
- Collaboration & Support: Work closely with analysts, data consumers, and business stakeholders to support data product delivery, troubleshoot data issues, and enable effective usage of Snowflake datasets.
- Enablement for Analytics & Data Science: Implement dimensional models that provide clean, well-structured, reusable datasets for reporting, scenario modelling, and emerging ML/AI use cases.
- Monitoring, Reliability & Operations: Implement and maintain monitoring, alerting, logging, and cost-management processes for Snowflake and data pipelines to ensure a stable and well-maintained platform.
- Continuous Improvement of Engineering Practices: Contribute to shared engineering standards to simplify development and accelerate delivery across the team.
Knowledge & Skills
- Proven experience in delivering cloud-based data engineering solutions, ideally with Snowflake.
- Strong hands‑on proficiency with SQL, Python, and dbt for data transformations, modelling, and pipeline automation.
- Practical experience with Snowflake and RBAC management.
- Experience with data ingestion and replication tools such as Airbyte, Fivetran, Hevo, or similar.
- Working knowledge of cloud services (AWS preferred).
- Strong understanding of data modelling and data governance principles.
- Experience supporting BI/reporting tools (Power BI) and enabling them through well‑designed Snowflake data models.
- Solid knowledge of CI/CD and version‑controlled development practices in git.
Desirable
- Enterprise System Familiarity: Exposure to CRM (Salesforce), BSS/OSS (Netadmin), Call Centre, Telephony, or similar enterprise data sources.
- Data Migration Experience: Participation in migrating data platforms (e.g., PostgreSQL or other cloud RDBMS) into a data warehouse like Snowflake with minimal disruption and strong data validation controls.
- Change & Adoption Support: Experience supporting business teams during platform transitions (e.g., training, documentation, user onboarding, issue resolution).
- Best Practice Contribution: Experience contributing to naming conventions, schema standards, environment management, testing frameworks, and security patterns for data platforms.
- Continuous Learning & Innovation: Interest in staying up to date with the latest technologies, modern data stack tooling, and best practices to contribute to ongoing platform evolution.
- Infrastructure as Code: Exposure to Terraform would be advantageous.
Gigaclear is a growing Fibre Broadband (FTTP / FTTH) company, developing our fibre‑to‑the‑premises broadband infrastructure to some of the most difficult to reach areas of the UK, empowering those communities with broadband to rival any city.
Senior Data Engineer in Abingdon employer: Gigaclear plc
At Gigaclear, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Data Engineer, you will have the opportunity to work with cutting-edge technologies in a supportive environment that prioritises employee growth and development. Our commitment to empowering communities through advanced broadband solutions not only makes your work meaningful but also positions you at the forefront of transforming connectivity across the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in Abingdon
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Snowflake. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data pipelines and models. Use GitHub or a personal website to highlight your projects, especially those involving SQL, Python, and dbt.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss how you've tackled performance optimisation and data quality checks in past roles—real examples go a long way!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Engineer in Abingdon
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Snowflake, SQL, and Python, and showcase any relevant projects that demonstrate your skills in building data pipelines and optimising performance.
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 mission at StudySmarter. Don’t forget to mention specific tools and methodologies you’ve used that relate to the job description.
Showcase Your Problem-Solving Skills:In your application, include examples of how you've tackled complex data challenges in the past. We love seeing candidates who can think critically and come up with innovative solutions, especially when it comes to data quality and governance.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Gigaclear plc
✨Know Your Snowflake Inside Out
Make sure you brush up on your Snowflake knowledge before the interview. Understand its architecture, features, and best practices. Be ready to discuss how you've used Snowflake in past projects, especially around data pipelines and performance optimisation.
✨Showcase Your Data Engineering Skills
Prepare to demonstrate your hands-on experience with SQL, Python, and dbt. Have examples ready that highlight your ability to build and maintain scalable data pipelines. Discuss any challenges you've faced and how you overcame them to ensure data quality and governance.
✨Familiarise Yourself with the Business Context
Research Gigaclear and understand their business model and the importance of data in their operations. Be prepared to explain how your role as a Senior Data Engineer can directly impact their analytics and reporting needs, helping them make data-driven decisions.
✨Emphasise Collaboration and Communication
Since you'll be working closely with analysts and stakeholders, highlight your experience in collaboration. Share examples of how you've supported teams in troubleshooting data issues or enabling effective usage of datasets, showcasing your ability to communicate complex technical concepts clearly.
