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- Tasks: Design and build data pipelines for AI/ML projects using Azure technologies.
- Company: Join a leading consulting firm focused on digital financial services and innovation.
- Benefits: Enjoy competitive rates, flexible working arrangements, and opportunities for professional growth.
- Why this job: Be part of cutting-edge AI/ML projects that make a real impact in the fintech industry.
- Qualifications: Azure Data Engineer certification and experience with machine learning frameworks required.
- Other info: This role is inside IR35; rates will reflect your expertise.
The predicted salary is between 48000 - 84000 £ per year.
Staffworx are planning for future talent pool projects. Azure Data Engineer with AI / Machine Learning experience for a leading specialist consulting organisation and Digital FS Fintech client.
Key Responsibilities:
- Excellent experience in the Data Engineering Lifecycle, creating data pipelines which take data through all layers from generation, ingestion, transformation and serving.
- Strong experience in building data solutions using Azure, Azure Data Lake Storage Gen2, Azure Databricks, Azure Data Factory, Azure Synapse, Data Fabric.
- Azure certified Data Engineer / Architect.
- Knowledge of Machine Learning and NLP unstructured data.
- Implemented ML platform in enterprise client experience of ML use-cases.
- AIML Platforms: DataRobot, Dataiku, Anaconda, Sagemaker, Vertex etc.
- AIML Frameworks: MLFlow, KubeFlow, BentoML, TensorFlow etc.
- AIML Development: PyTorch, Jupyter Notebooks, XGBoost, Tensorflow etc.
- AIML Models: Linear/Logistic Regression, KNN, Decision Trees, Anomaly Detection, LLMs, Generative Models (PALM, GPT3/4), Entity Extraction etc.
Inside IR35 contract, rates to reflect.
Azure Data Engineer (AI / ML) employer: Staffworx
Contact Detail:
Staffworx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Engineer (AI / ML)
✨Tip Number 1
Network with professionals in the Azure and AI/ML fields. Attend industry meetups, webinars, or conferences to connect with potential colleagues and employers. This can help you gain insights into the latest trends and job openings.
✨Tip Number 2
Showcase your hands-on experience with Azure tools by contributing to open-source projects or creating your own projects. This practical experience can set you apart from other candidates and demonstrate your skills effectively.
✨Tip Number 3
Stay updated on the latest developments in AI and machine learning frameworks. Follow relevant blogs, podcasts, and online courses to enhance your knowledge and skills, making you a more attractive candidate for the role.
✨Tip Number 4
Prepare for technical interviews by practising common data engineering and machine learning problems. Use platforms like LeetCode or HackerRank to sharpen your coding skills and get comfortable with problem-solving under pressure.
We think you need these skills to ace Azure Data Engineer (AI / ML)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with the Data Engineering Lifecycle and specific Azure tools mentioned in the job description. Use keywords like 'Azure Data Lake Storage Gen2', 'Azure Databricks', and 'Machine Learning' to catch the recruiter's attention.
Craft a Compelling Cover Letter: In your cover letter, explain how your background aligns with the responsibilities of the Azure Data Engineer role. Mention specific projects where you've built data pipelines or implemented ML solutions, showcasing your hands-on experience with relevant technologies.
Showcase Relevant Projects: If you have worked on any projects involving AI/ML platforms or frameworks like TensorFlow or PyTorch, be sure to include these in your application. Describe your role and the impact of your contributions to demonstrate your expertise.
Highlight Certifications: If you hold any Azure certifications, such as Azure Data Engineer or Architect, make them prominent in your application. This not only validates your skills but also shows your commitment to professional development in the field.
How to prepare for a job interview at Staffworx
✨Showcase Your Data Engineering Experience
Be prepared to discuss your experience with the entire Data Engineering Lifecycle. Highlight specific projects where you've created data pipelines, detailing the processes of generation, ingestion, transformation, and serving.
✨Demonstrate Azure Proficiency
Familiarise yourself with the Azure tools mentioned in the job description, such as Azure Data Lake Storage Gen2 and Azure Databricks. Be ready to explain how you've used these tools in past projects and the impact they had on your work.
✨Discuss Machine Learning Knowledge
Since the role requires knowledge of Machine Learning and NLP, prepare to talk about your experience with ML platforms and frameworks. Bring examples of ML use-cases you've implemented and be ready to discuss the models you've worked with.
✨Prepare for Technical Questions
Expect technical questions related to data engineering and machine learning. Brush up on key concepts and be ready to solve problems on the spot, demonstrating your analytical thinking and problem-solving skills.
