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For Companies At a Glance
- Tasks: Lead data initiatives and shape how critical data is managed and analysed.
- Company: Join a leading organisation on an exciting Proof of Concept project.
- Benefits: Competitive daily rate, hybrid work model, and potential for extension.
- Why this job: Make a significant impact on data processes in a high-stakes environment.
- Qualifications: Experience in data engineering and strong analytical skills.
- Other info: Opportunity to work with cutting-edge technology and grow your career.
The predicted salary is between 45000 - 75000 £ per year.
Overview
Job Title: Lead Data Engineer
Location: Leeds, 2x per week
Salary: Up to £80,000 per annum
Why Apply? This is an exciting opportunity to work as a Lead Data Engineer delivering scalable, high quality data solutions for a leading client in the technology sector. This position offers professional growth, challenging projects, and access to cutting edge cloud data technologies.
Responsibilities
- Design, develop, and optimise robust, scalable data pipelines and architectures to support business intelligence and analytics initiatives.
- Manage and maintain cloud-based data platforms (AWS, Azure, or Google Cloud) including data lakes, warehouses, and lakehouse solutions.
- Transform and process structured and unstructured data using modern ETL/ELT frameworks (Apache Spark, Airflow, dbt).
- Collaborate closely with product managers, analysts, and software developers to ensure seamless integration and high-quality data availability.
- Develop, maintain, and enhance reporting and analytics capabilities through tools such as PowerBI, Tableau, or QuickSight.
- Apply best practices in data governance, data quality, and performance optimisation.
- Operate in an agile environment, contributing to technical discussions and problem-solving initiatives.
- Proven experience in building and managing cloud-based data platforms (AWS Redshift/Glue, Azure Data Factory/Synapse, Google BigQuery/Dataflow).
- Strong programming skills in Python, SQL, and Java for data engineering tasks.
- Experience designing reliable, maintainable, and high-performance data pipelines and architectures.
- Broad understanding of data warehousing, data lakes, and lakehouse architectures.
- Familiarity with business intelligence and data visualisation tools.
- Excellent analytical thinking, attention to detail, and problem-solving skills.
- Strong collaboration and communication skills, able to work with both technical and non-technical stakeholders.
- Comfortable with complexity, ambiguity, and working independently or as part of a team in a fast-paced environment.
We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of their race, sex, disability, religion/belief, sexual orientation or age.
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Lead Data Engineer employer: Fruition Group
Contact Detail:
Fruition Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead on a role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those related to data extraction, transformation, and analysis. This will give potential employers a clear idea of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges and solutions. Be ready to discuss how you've tackled similar issues in the past, as this will demonstrate your expertise and problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic roles waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Lead Data Engineer. Focus on relevant projects and skills that align with the job description, especially around data extraction, transformation, and analysis.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of your past work that demonstrate your expertise and how you can contribute to our Proof of Concept project.
Showcase Your Technical Skills: Don’t forget to mention the tools and technologies you’re proficient in. We want to see your technical prowess, so list out any relevant programming languages, frameworks, or methodologies you've used in your previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates regarding your application status.
How to prepare for a job interview at Fruition Group
✨Know Your Data Inside Out
As a Lead Data Engineer, you’ll need to demonstrate your expertise in data extraction, transformation, and analysis. Brush up on the latest tools and technologies relevant to the role, and be ready to discuss specific projects where you've successfully implemented these skills.
✨Showcase Your Leadership Skills
Since this role involves being a Subject Matter Expert (SME), it’s crucial to highlight your leadership experience. Prepare examples of how you've led teams or projects, particularly in high-impact initiatives, and how you’ve influenced decision-making processes.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving abilities and knowledge of data engineering principles. Practice explaining complex concepts in simple terms, as you may need to communicate with non-technical stakeholders during the project.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the project. Inquire about the team dynamics, the specific challenges they face with data, and how success will be measured in this Proof of Concept project.
