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- Tasks: Lead data engineering projects, transforming raw data into actionable insights for clients.
- Company: Join a dynamic IT consultancy focused on solving real-world data challenges across various sectors.
- Benefits: Enjoy flexible working options, travel opportunities, and a collaborative team environment.
- Why this job: Be at the forefront of data innovation, using cutting-edge tools to make a real impact.
- Qualifications: Experience in IT consultancy, proficiency in Python, SQL, and big data tools required.
- Other info: This role involves some European travel, enhancing your professional experience.
The predicted salary is between 48000 - 72000 £ per year.
The ideal Lead Data Engineer will have a background from either an IT Technology provider or IT Consultancy and enjoys working with clients to solve real world data problems. In this exciting role, you'll partner with clients to transform raw data into powerful insights, ensuring top-tier performance, reliability, and compliance with data governance standards. The Lead Data Engineer will be well versed in the latest Data Tools / Gen AI and can utilise them to deliver high quality solutions that align with the clients' objectives.
To be considered for this role you will need some of the following:
- Experience from either an IT Technology provider or IT Consultancy background.
- Thrives working in a client facing environment and has a proven track record working across a range of sectors that include but are not limited to banking, insurance, healthcare, media, retail, infrastructure and telco.
- The ideal candidate will have expertise in some of the following: Python, SQL, Scala, and Java for data engineering.
- Strong experience with big data tools (Apache Spark, Hadoop, Databricks, Dask) and cloud platforms (AWS, Azure, GCP).
- Proficient in data modelling (relational, NoSQL, dimensional) and DevOps automation (Docker, Kubernetes, Terraform, CI/CD).
- Skilled in designing scalable, fault-tolerant data architectures.
- Strong focus on security and compliance, implementing RBAC, encryption, and auditing best practices.
- Strong problem-solving ability to debug and optimize data pipelines.
- Effective cross-functional collaborator with leadership experience in mentoring engineers and enforcing best practices.
NB - This role does have some European travel.
If you are an experienced Lead Data Engineer with the required skills, please respond to this ad in the first instance with an up to date version of your CV for review.
Contact Detail:
Mccabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Lead
✨Tip Number 1
Familiarise yourself with the latest data tools and technologies mentioned in the job description, such as Apache Spark and AWS. Being able to discuss these tools confidently during your interview will show that you're up-to-date and ready to hit the ground running.
✨Tip Number 2
Highlight your experience in client-facing roles, especially if you've worked across various sectors like banking or healthcare. Prepare specific examples of how you've solved real-world data problems for clients, as this will demonstrate your ability to thrive in a similar environment at StudySmarter.
✨Tip Number 3
Showcase your leadership skills by discussing any mentoring or team collaboration experiences. We value effective cross-functional collaboration, so be ready to explain how you've led teams or enforced best practices in previous roles.
✨Tip Number 4
Prepare to discuss your problem-solving abilities, particularly in debugging and optimising data pipelines. Think of specific challenges you've faced and how you overcame them, as this will highlight your analytical skills and readiness for the role.
We think you need these skills to ace Data Engineering Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in IT technology or consultancy, especially focusing on client-facing roles. Emphasise your expertise in Python, SQL, and big data tools like Apache Spark and Hadoop.
Showcase Relevant Experience: In your application, detail your experience across various sectors such as banking, healthcare, and retail. Provide specific examples of how you've solved real-world data problems for clients.
Highlight Technical Skills: Clearly list your technical skills related to data engineering, including cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes). Mention any experience with data modelling and security best practices.
Express Your Leadership Qualities: If you have experience mentoring engineers or leading teams, make sure to include this in your application. Highlight your ability to enforce best practices and collaborate effectively across functions.
How to prepare for a job interview at Mccabe & Barton
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, Scala, and Java. Highlight specific projects where you used big data tools like Apache Spark or cloud platforms such as AWS, Azure, or GCP.
✨Demonstrate Client-Facing Experience
Since the role involves working closely with clients, share examples of how you've successfully collaborated with clients in previous roles. Discuss any challenges you faced and how you overcame them.
✨Emphasise Problem-Solving Abilities
Prepare to talk about specific instances where you debugged and optimised data pipelines. Use metrics or outcomes to illustrate the impact of your solutions.
✨Discuss Data Governance and Security
Given the focus on compliance and security, be ready to explain your understanding of data governance standards. Share experiences where you implemented best practices for security, such as RBAC and encryption.
