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For Companies At a Glance
- Tasks: Build scalable data pipelines and manage data infrastructure in Azure.
- Company: Join a rapidly expanding data consultancy focused on impactful solutions.
- Benefits: Enjoy hybrid working, 35 days holiday, pension scheme, and ongoing training.
- Why this job: Work on diverse projects for impressive clients in a supportive, innovative culture.
- Qualifications: 2+ years of data engineering experience with skills in Python, SQL, and Azure.
- Other info: Diversity is valued; all backgrounds are encouraged to apply.
The predicted salary is between 42500 - 57500 £ per year.
Overview
Location: South Derbyshire area (Hybrid)
Type: Permanent
A growing, data-driven organisation is investing in modern tooling and building out its cloud data platform. With a collaborative data team of 19 and a clear roadmap in place, this is a great time to get involved and go on the journey with a business in the early stages of deploying its Azure data stack.
About you
This role suits a Data Engineer with 3+ years’ experience who enjoys hands-on engineering work and wants to support the design and build of a modern platform while continuing to learn and develop in a supportive, team-first environment.
The opportunity
- Join a supportive, collaborative and growing data & analytics team
- Contribute to the rollout of a modern Azure data platform
- Support the design and build of scalable data pipelines
- Work closely with analysts and stakeholders on real use cases
- Gain exposure to platform architecture and engineering best practice
- Be part of a long-term data maturity journey
What you’ll be doing
- Building and maintaining cloud-based data pipelines
- Supporting the design and implementation of the Azure data platform
- Developing data transformation and integration workflows
- Applying good data modelling and warehousing practices
- Supporting data quality, testing and technical documentation
- Collaborating with analytics and business teams to translate requirements into solutions
Experience we’re looking for
- Around 3+ years’ experience in a data engineering or similar role
- Hands-on experience with Microsoft Azure data services
- Exposure to tools such as Azure Data Factory, Data Lake, Synapse and/or Databricks
- Strong SQL and working knowledge of Python
- Understanding of core data modelling and warehousing concepts
- Experience working with multiple data sources
- Collaborative mindset and strong problem-solving approach
Nice to have
- Exposure to CI/CD or DevOps practices
- Experience working with APIs and integration patterns
- Experience with semi-structured data such as JSON or XML
This is an excellent opportunity for someone who wants to grow with a modern data function, contribute to platform design, and deepen their Azure engineering capability within a genuinely collaborative team.
Mirai believes in the power of diversity and the importance of an inclusive culture. We welcome applications from people of all backgrounds and experiences, recognising that different perspectives make teams stronger and outcomes better. This is one of the ways we take positive action to help shape a more collaborative and diverse future in the workplace
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Data Engineer employer: Mirai Talent
Contact Detail:
Mirai Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Azure Data Factory, Databricks, and PySpark. Having hands-on experience or projects showcasing these skills can set you apart during discussions.
✨Tip Number 2
Network with current employees or professionals in the data engineering field, especially those who work with Azure. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your problem-solving approach in detail. The company values pragmatic solutions, so be ready to share examples of how you've tackled complex data challenges in previous roles.
✨Tip Number 4
Showcase your communication skills by practising explaining technical concepts in simple terms. This will demonstrate your ability to bridge the gap between technical and non-technical stakeholders, which is crucial for the role.
We think you need these skills to ace Data 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. Use specific examples of projects where you've built data pipelines or managed data infrastructure.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with the company's mission. Mention your experience with ETL tools and cloud platforms, and how you can contribute to their innovative projects.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, such as proficiency in PySpark, data modelling techniques, and automation scripting. This will help demonstrate your fit for the role.
Highlight Problem-Solving Abilities: Provide examples of how you've solved complex data challenges in previous roles. This could include optimising data pipelines or improving data quality, showcasing your pragmatic approach to problem-solving.
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 managed data infrastructure, especially in Azure environments.
✨Demonstrate Problem-Solving Abilities
The company values pragmatic problem solvers. Be ready to share specific instances where you balanced technical solutions with business needs, highlighting your approach to overcoming challenges.
✨Communicate Clearly
As an excellent communicator, you should practice explaining complex data concepts in simple terms. This will show your ability to collaborate effectively with both technical and non-technical team members.
✨Emphasise Continuous Learning
The organisation prioritises growth and learning. Share how you stay updated with the latest technologies and methodologies in data engineering, and express your enthusiasm for ongoing training opportunities.
