At a Glance
- Tasks: Design and build secure, scalable data platforms using cutting-edge technologies.
- Company: Join a forward-thinking firm focused on data innovation and compliance.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact by developing robust data solutions that drive business success.
- Qualifications: Degree in Computer Science or related field; experience with Azure and data engineering.
The predicted salary is between 70000 - 90000 £ per year.
The Data Platform Engineer designs, develops, automates, and maintains secure, scalable, and compliant data platforms that enable the firm to efficiently manage, analyse, and utilise data. The role ensures that data solutions are robust and reliable while meeting regulatory obligations and safeguarding client confidentiality.
Key Responsibilities
- Design and architect scalable, secure, and compliant data platforms and solutions, producing technical documentation and securing approvals through governance bodies such as Architecture Review Boards.
- Build and deliver robust data solutions using Databricks, PySpark, Spark SQL, Azure Data Factory, and Azure services.
- Develop APIs and write efficient Python, PySpark, and SQL code to support data integration, processing, and automation.
- Implement and manage CI/CD pipelines and automated deployments using Azure DevOps to enable reliable releases across environments.
- Develop and maintain infrastructure-as-code (eg, Terraform, ARM) to provision and manage cloud resources, including ADF pipelines, Databricks assets, and Unity Catalog components.
- Monitor, troubleshoot, and optimise data platform performance, reliability, and costs, identifying bottlenecks and recommending improvements.
- Create dashboards and observability tools to report on platform performance, usage, incidents, and operational KPIs.
Knowledge, Skills & Experience
- Degree in Computer Science, Data Engineering, or a related field.
- Proven experience designing and building cloud-based data platforms, ideally within Azure.
- Strong hands‑on expertise with Databricks, PySpark, Spark SQL, and Azure Data Factory.
- Solid understanding of Data Lakehouse architecture and modern data platform design.
- Proficiency in Python for data engineering, automation, and data processing.
- Experience developing and integrating REST APIs for data services.
- Strong DevOps experience, including CI/CD, automated testing, and release management for data platforms.
- Experience with Infrastructure as Code tools such as Terraform or ARM templates.
- Knowledge of data modelling, ETL/ELT pipelines, and data warehousing concepts.
- Familiarity with monitoring, logging, and alerting tools (eg, Azure Monitor).
Desirable
- Experience with additional Azure services (eg, Fabric, Azure Functions, Logic Apps).
- Knowledge of cloud cost optimisation for data platforms.
- Understanding of data governance and regulatory compliance (eg, GDPR).
- Experience working in regulated or professional services environments.
Lead Data Platform Engineer - Databricks - IAC - Terraform - Azure Data Factory - Data Lakehous[...] employer: Energy Jobline ZR
As a Lead Data Platform Engineer, you will thrive in a dynamic and innovative environment that prioritises employee growth and collaboration. Our company offers competitive benefits, a strong commitment to work-life balance, and opportunities for professional development, all while working with cutting-edge technologies in the heart of a vibrant tech hub. Join us to be part of a culture that values creativity, teamwork, and the pursuit of excellence in data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Platform Engineer - Databricks - IAC - Terraform - Azure Data Factory - Data Lakehous[...]
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks and Azure. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to data platforms and cloud services. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing passionate candidates who are eager to join our team!
We think you need these skills to ace Lead Data Platform Engineer - Databricks - IAC - Terraform - Azure Data Factory - Data Lakehous[...]
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Lead Data Platform Engineer. Highlight your experience with Databricks, Azure Data Factory, and Terraform. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data platforms and how your background makes you a perfect fit for us. Keep it engaging and relevant to the job description.
Showcase Your Projects:If you've worked on any cool projects involving data engineering or cloud platforms, make sure to mention them! We love seeing real-world applications of your skills, especially if they relate to the technologies we use.
Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Tech Inside Out
Make sure you’re well-versed in Databricks, PySpark, and Azure Data Factory. Brush up on your knowledge of data lakehouse architecture and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data platform design or performance optimisation. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Demonstrate Your DevOps Know-How
Be ready to talk about your experience with CI/CD pipelines and Infrastructure as Code tools like Terraform. Highlight any projects where you’ve implemented automated deployments and how it improved efficiency.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, governance practices, and team dynamics. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
