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- Tasks: Build scalable data pipelines and manage data infrastructure across cloud environments.
- Company: Join a rapidly expanding data consultancy focused on impactful data solutions.
- Benefits: Enjoy hybrid working, 35 days holiday, pension scheme, and ongoing training.
- Why this job: Work on diverse projects for impressive clients while fostering innovation and collaboration.
- Qualifications: 5+ years in data engineering with strong skills in Python, SQL, and Azure.
- Other info: Mirai values diversity and promotes an inclusive culture.
The predicted salary is between 28800 - 42000 £ per year.
The company is an ambitious, innovative, and rapidly expanding data consultancy dedicated to delivering impactful data solutions for a diverse client portfolio. The culture is built on collaboration, continuous learning, and making a real difference through data-driven insights.
Work on high-impact, diverse projects for impressive clients across finance, retail, manufacturing, and technology sectors. Be part of a supportive team that values innovation, expertise, and professional development. Benefit from a flexible hybrid working model with remote and on-site options. Enjoy a comprehensive package including 35 days holiday plus bank holidays, pension scheme, and ongoing training opportunities.
The company is looking for a talented Data Engineer to join the technical team. The successful candidate will be responsible for building scalable, reliable data pipelines, managing data infrastructure, and supporting data products across various cloud environments, primarily Azure.
- Develop end-to-end data pipelines using Python, Databricks, PySpark, and SQL.
- Integrate data from various sources including APIs, Excel, CSV, JSON, and databases.
- Manage data lakes, warehouses, and lakehouses within Azure cloud environments.
- Apply data modelling techniques such as Kimball methodologies, star schemas, and data warehouse design principles.
- Build and support ETL workflows using tools like Azure Data Factory, Synapse, Delta Live Tables, dbt, SSIS, etc.
- Automate infrastructure deployment with Terraform, ARM, or Bicep.
- Collaborate on report development and visualisation with Power BI.
- Manage version control and deployment pipelines using Git, Azure DevOps, or GitHub.
- Contribute to the development of applications and APIs supporting data workflows.
- Promote best practices regarding code quality, testing, observability, and operational stability.
5+ years of practical data engineering experience. Has strong skills in Python, SQL, and PySpark. Experienced working with data lakes, warehouses, lakehouses, and cloud platforms, preferably Azure. Knowledgeable in data modelling, including Kimball and star schemas. Familiar with ETL tools such as Azure Data Factory, Synapse, Delta Live Tables, dbt, SSIS. Skilled in Power BI report development. Knowledge of DevOps, MLOps, and LLMOps is desirable. Experienced in application and API development is an advantage.
Confident in owning full data pipelines from ingestion to deployment. Passionate about maintaining high standards for code quality, testing, and operational observability.
Hybrid working model (Greater Manchester-based office). ~35 days holiday plus bank holidays. ~ Opportunity to work on high-impact projects with an impressive client base. ~ Mirai believes in the power of diversity and the importance of an inclusive culture.
Locations
Contact Detail:
Mirai Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Science Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Azure Data Factory, Databricks, and Power BI. Having hands-on experience or projects showcasing these skills can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with Azure. Attend meetups, webinars, or online forums to connect with industry experts and gain insights into the latest trends and best practices.
✨Tip Number 3
Showcase your passion for continuous learning by engaging in relevant online courses or certifications related to data engineering and cloud platforms. This demonstrates your commitment to professional development, which aligns with the company's values.
✨Tip Number 4
Prepare to discuss your previous projects in detail during interviews, focusing on your role in building data pipelines and managing data infrastructure. Be ready to explain your thought process and the impact of your work on the overall project outcomes.
We think you need these skills to ace Junior Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with Python, SQL, and Azure. Emphasise any projects where you've built data pipelines or worked with ETL tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the company's mission. Mention specific projects or experiences that align with their focus on impactful data solutions.
Showcase Technical Skills: In your application, clearly outline your technical skills related to data modelling, cloud environments, and tools like Azure Data Factory and Power BI. Use examples to demonstrate your proficiency.
Highlight Collaborative Experience: Since the company values collaboration, include examples of how you've worked effectively in teams. Discuss any experiences where you contributed to high-impact projects or supported colleagues in achieving shared goals.
How to prepare for a job interview at Mirai Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and PySpark in detail. Bring examples of projects where you've built data pipelines or worked with cloud environments, especially Azure, as this will demonstrate your hands-on expertise.
✨Understand Data Modelling Techniques
Familiarise yourself with Kimball methodologies and star schemas. Be ready to explain how you've applied these techniques in past projects, as this knowledge is crucial for the role.
✨Demonstrate Collaboration and Communication
Since the company values teamwork, be prepared to discuss how you've collaborated on projects in the past. Highlight any experience you have with report development and visualisation tools like Power BI, as well as your approach to working within a team.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects, culture, and future goals. This shows your genuine interest in the role and helps you assess if the company aligns with your career aspirations.
