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- Tasks: Lead data engineering projects and architect modern data platforms on Azure.
- Company: Join a forward-thinking tech company focused on innovative data solutions.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Shape the future of data engineering and mentor teams in a dynamic environment.
- Qualifications: 12-16 years in IT with strong Azure and data architecture expertise.
- Other info: Collaborative culture with a focus on cutting-edge technology and career advancement.
The predicted salary is between 80000 - 100000 £ per year.
We are looking for a strong Data Engineering Architect with 12–16 years of experience in building and architecting modern data platforms on Microsoft Azure. The ideal candidate will have deep hands‑on expertise in Azure Data Factory (ADF) pipeline engineering, SQL performance tuning, and end‑to‑end data integration architecture, along with a strong analytical mindset to troubleshoot complex data issues. You will lead solution architecture, define best practices, and mentor teams to build scalable, secure, and reliable data solutions.
Responsibilities
- Lead solution architecture for data engineering projects.
- Define and enforce best practices for data platform design.
- Mentor and guide teams in building scalable, secure, and reliable data solutions.
- Resolve complex multi‑system data issues and provide troubleshooting expertise.
Required Skills & Qualifications
- 12–16 years of overall IT experience with significant data engineering and architecture exposure.
- Strong Azure Cloud Data Engineering and associated services architecture knowledge.
- Deep hands‑on experience with Azure Data Factory (ADF) – pipeline design, orchestration, integration runtime.
- Advanced SQL skills – querying, stored procedures, performance tuning.
- Strong troubleshooting skills for complex multi‑system data issues.
- Solid understanding of data architecture concepts: data lakes/lakehouse/warehouse, dimensional modeling, ELT/ETL patterns.
- Experience with batch orchestration, dependency management, SCD handling, incremental loads.
- Knowledge of Azure Monitor, Log Analytics, Application Insights for monitoring and observability.
- Familiarity with Azure AD, Managed Identity, Key Vault, RBAC for security and identity.
- Experience with CI/CD practices for data pipelines, Git branching strategies, and release governance.
- Strong documentation skills: architecture diagrams, solution designs, operational runbooks.
Preferred / Good to Have Skills
- Experience with Azure Synapse Analytics / Dedicated SQL Pools.
- Experience with Azure Databricks / Spark.
- Experience with ADLS Gen2, Azure SQL DB, Managed Instance.
- Experience with Event Hub / Kafka, Stream Analytics (if real‑time involved).
Data Engineering Architect in Stratford-upon-Avon employer: Test Yantra
Contact Detail:
Test Yantra Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Architect in Stratford-upon-Avon
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure Data Factory and SQL performance tuning. This will give potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss how you've tackled complex data issues in the past. We want to see your analytical mindset in action!
✨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 Data Engineering Architect in Stratford-upon-Avon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience with Azure Data Factory and SQL performance tuning. We want to see how your skills align with the role, so don’t be shy about showcasing your relevant projects!
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 makes you the perfect fit for our team. We love seeing enthusiasm and a personal touch.
Showcase Your Problem-Solving Skills: In your application, give examples of complex data issues you've resolved in the past. We’re looking for candidates who can troubleshoot effectively, so share those success stories that demonstrate your analytical mindset!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Test Yantra
✨Know Your Azure Inside Out
Make sure you brush up on your Azure Data Factory skills and other Azure services mentioned in the job description. Be ready to discuss specific projects where you've implemented ADF pipelines or tackled SQL performance tuning. This will show that you not only understand the theory but have practical experience too.
✨Showcase Your Troubleshooting Skills
Prepare to share examples of complex data issues you've resolved in the past. Think about the challenges you faced, the steps you took to troubleshoot, and the outcomes. This will demonstrate your analytical mindset and problem-solving abilities, which are crucial for this role.
✨Highlight Your Mentorship Experience
Since mentoring is a key part of the role, be ready to talk about how you've guided teams in the past. Share specific instances where you defined best practices or helped others improve their skills. This will show that you're not just a technical expert but also a team player.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that test your knowledge of data architecture concepts and CI/CD practices. Think through how you would approach designing a scalable data solution or managing dependencies in a pipeline. Practising these scenarios will help you articulate your thought process clearly during the interview.