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- Tasks: Design and maintain data pipelines using Azure services for analytics.
- Company: Join a dynamic team focused on innovative data solutions.
- Benefits: Enjoy hybrid work options and competitive salary between £55,000-£65,000.
- Why this job: Be part of a collaborative culture that values data-driven decision-making.
- Qualifications: Strong experience with Azure tools and data engineering principles required.
- Other info: Ideal for those passionate about data security and compliance.
The predicted salary is between 47000 - 78000 £ per year.
My client is looking for a highly skilled Data Engineer to join our growing data team. This role is ideal for someone with strong experience in Azure data services and a passion for building scalable, secure, and cost-effective data pipelines that support analytics and BI initiatives. You’ll work closely with data scientists, analysts, and business stakeholders to ensure our data infrastructure is reliable, performant, and compliant.
Key Responsibilities
- Design, build, and maintain robust ETL/ELT pipelines using Azure Data Factory, Synapse Analytics, and Data Lake Storage.
- Model data for analytical and BI consumption, including normalized and denormalized schemas.
- Collaborate with stakeholders to gather data requirements and translate them into efficient engineering solutions.
- Monitor and optimize cloud costs, query performance, and storage efficiency.
- Ensure data architecture and processes meet security, privacy, and compliance standards (e.g., GDPR, encryption, access controls).
- Support CI/CD and data pipeline automation best practices.
Must-Have Skills
- Strong hands-on experience with Azure Synapse Analytics, Data Factory, and Data Lake Storage.
- Proven ability to build and manage ETL pipelines from various structured and unstructured sources.
- Expertise in SQL and data modeling for analytics.
- Experience with cloud cost optimization strategies and working within fixed budgets.
- Solid understanding of data security, GDPR, access control, and encryption best practices.
Nice-to-Have Skills
- Exposure to AWS Redshift, Glue, or Snowflake.
- Familiarity with BigQuery and Google Analytics APIs.
- Proficiency in Python, PySpark, or dbt for data transformations.
- Background in insurance, especially in pricing analytics or actuarial data.
Data Engineer - Salisbury - £55,000-£65,000 - Hybrid employer: Ascentia Partners
Contact Detail:
Ascentia Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Salisbury - £55,000-£65,000 - Hybrid
✨Tip Number 1
Familiarise yourself with Azure data services, especially Azure Synapse Analytics and Data Factory. Consider building a small project or contributing to open-source projects that utilise these tools to showcase your hands-on experience.
✨Tip Number 2
Network with professionals in the data engineering field, particularly those who work with Azure technologies. Attend meetups or webinars to connect with potential colleagues and learn about industry trends that could give you an edge.
✨Tip Number 3
Stay updated on best practices for data security and compliance, especially GDPR. Being knowledgeable about these regulations will not only help you in interviews but also demonstrate your commitment to responsible data management.
✨Tip Number 4
Prepare to discuss your experience with cost optimisation strategies in cloud environments. Be ready to share specific examples of how you've managed budgets and improved efficiency in previous roles.
We think you need these skills to ace Data Engineer - Salisbury - £55,000-£65,000 - Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure data services, ETL/ELT pipelines, and any relevant projects. Use keywords from the job description to demonstrate that you meet the requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with the company's needs. Mention specific experiences that showcase your ability to build scalable data pipelines and collaborate with stakeholders.
Showcase Relevant Projects: If you have worked on projects involving Azure Synapse Analytics or Data Factory, include these in your application. Briefly describe your role, the challenges faced, and the outcomes achieved to illustrate your expertise.
Highlight Compliance Knowledge: Since the role requires knowledge of data security and compliance standards, mention any relevant experience you have with GDPR, encryption, or access controls. This will show that you understand the importance of these aspects in data engineering.
How to prepare for a job interview at Ascentia Partners
✨Showcase Your Azure Expertise
Make sure to highlight your hands-on experience with Azure Synapse Analytics, Data Factory, and Data Lake Storage. Prepare specific examples of projects where you successfully built and managed ETL pipelines, as this will demonstrate your technical skills effectively.
✨Understand Data Modelling
Be ready to discuss your approach to data modelling for analytics. Explain the differences between normalized and denormalized schemas and provide examples of how you've implemented these in past roles. This shows your depth of knowledge in data architecture.
✨Discuss Cost Optimisation Strategies
Since the role involves monitoring and optimising cloud costs, come prepared with strategies you've used in the past. Discuss how you've managed budgets while ensuring performance and efficiency, which will resonate well with the interviewers.
✨Emphasise Compliance Knowledge
Data security and compliance are crucial in this role. Be prepared to talk about your understanding of GDPR, encryption, and access controls. Sharing specific instances where you ensured compliance in your previous work will strengthen your candidacy.
