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- 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.
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Data Engineer – Growing Data & AnalyticsConsultancy
Location: Greater Manchester (Hybrid)
Salary: £50,000 – £60,000 with excellent benefits
About the Company:
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. The organisation prioritises a supportive environment that encourages growth, practical problem-solving, and technical excellence.
Why Join the Company:
- 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.
Data Engineer (2+ Years of Experience)
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.
Key Responsibilities:
- 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.
- Use scripting (PowerShell/Bash) for automation tasks.
- Contribute to the development of applications and APIs supporting data workflows.
- Promote best practices regarding code quality, testing, observability, and operational stability.
Ideal Candidate:
- Possesses 2+ 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.
- Experienced with Infrastructure as Code (Terraform, ARM, Bicep).
- Skilled in Power BI report development.
- Proficient in version control and CI/CD practices.
- Capable of scripting automation with PowerShell or Bash.
- Knowledge of DevOps, MLOps, and LLMOps is desirable.
- Experienced in application and API development is an advantage.
What They Are Looking For:
- A pragmatic problem solver who balances technical solutions with business requirements.
- Confident in owning full data pipelines from ingestion to deployment.
- An excellent communicator capable of explaining complex concepts clearly.
- Passionate about maintaining high standards for code quality, testing, and operational observability.
What’s on Offer
- Hybrid working model (Greater Manchester-based office).
- Opportunity to work on high-impact projects with an impressive client base.
- A supportive and collaborative culture with a focus on innovation and growth.
Mirai believes in the power of diversity and the importance of an inclusive culture. They welcome applications from individuals of all backgrounds, understanding that a range of perspectives strengthens both their team and their partners’ teams. This is just one of the ways that they’re taking positive action to shape a 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.
