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- Tasks: Design and maintain data pipelines for analytics using Azure services.
- Company: Join a dynamic team focused on innovative data solutions in Salisbury.
- 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 and innovation.
- Qualifications: Strong experience with Azure, SQL, and data modelling required; Python skills are a plus.
- Other info: Ideal for those with a background in insurance or pricing analytics.
The predicted salary is between 44000 - 52000 £ 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.
- 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.
- Support CI/CD and data pipeline automation best practices.
Strong hands-on experience with Azure Synapse Analytics, Data Factory, and Data Lake Storage. Expertise in SQL and data modeling for analytics. Solid understanding of data security, GDPR, access control, and encryption best practices. Exposure to AWS Redshift, Glue, or Snowflake. Proficiency in Python, PySpark, or dbt for data transformations. Background in insurance, especially in pricing analytics or actuarial data.
Data Engineer (AWS, SQL) employer: Ascentia Partners
Contact Detail:
Ascentia Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (AWS, SQL)
✨Tip Number 1
Familiarise yourself with Azure data services, especially Azure Data Factory and Synapse Analytics. Having hands-on experience or projects showcasing your skills in these areas will make you stand out to our hiring team.
✨Tip Number 2
Brush up on your SQL skills and be prepared to discuss your experience with data modelling for analytics. Being able to articulate how you've designed schemas for both normalised and denormalised data will impress us.
✨Tip Number 3
Understand the importance of data security and compliance, particularly GDPR. Be ready to share examples of how you've implemented security measures in your previous roles, as this is crucial for our data architecture.
✨Tip Number 4
If you have experience with AWS tools like Redshift or Glue, make sure to highlight that. Even if your primary focus has been on Azure, showing familiarity with other cloud platforms can demonstrate your versatility and adaptability.
We think you need these skills to ace Data Engineer (AWS, SQL)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure data services, SQL, and any relevant tools like Azure Data Factory and Synapse Analytics. Use specific examples to demonstrate your skills in building ETL/ELT pipelines and data modelling.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your background aligns with the company's needs. Mention your experience with cloud cost optimisation and compliance standards, as well as your familiarity with AWS tools if applicable.
Showcase Relevant Projects: If you have worked on projects involving data pipelines or analytics, include them in your application. Describe your role, the technologies used, and the impact of your work on the project's success.
Highlight Soft Skills: Data Engineers often collaborate with various stakeholders. Emphasise your communication skills and ability to gather requirements effectively. Mention any experience working in cross-functional teams to showcase your collaborative spirit.
How to prepare for a job interview at Ascentia Partners
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Azure Synapse Analytics, Data Factory, and Data Lake Storage. Highlight specific projects where you've built ETL/ELT pipelines and how you optimised them for performance and cost.
✨Understand the Business Context
Familiarise yourself with the insurance industry, especially in pricing analytics or actuarial data. Demonstrating an understanding of how data engineering supports business objectives will impress your interviewers.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills. Be ready to explain how you would gather data requirements from stakeholders and translate them into engineering solutions, as well as how you would ensure compliance with security and privacy standards.
✨Demonstrate Collaboration Skills
Since you'll be working closely with data scientists, analysts, and business stakeholders, share examples of past collaborations. Discuss how you effectively communicated technical concepts to non-technical team members and contributed to a successful project outcome.
