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For Companies At a Glance
- Tasks: Lead the design and optimisation of a real-time data platform.
- Company: Join a high-growth digital business focused on engineering and data innovation.
- Benefits: Enjoy hybrid working, private healthcare, and regular team socials.
- Why this job: Shape a new function with cutting-edge technology and a collaborative culture.
- Qualifications: Experience with streaming data platforms and proficiency in Python, Java, or Scala required.
- Other info: Opportunity to work on greenfield tech and influence strategic decisions.
The predicted salary is between 43200 - 72000 £ per year.
We are working with a high-growth digital business that’s investing heavily in its internal engineering and data function. As they continue scaling their operations across multiple markets, they’re looking to bring on an experienced Lead Data Engineer to help shape a brand-new, real-time data platform.
About the Role
This is a hands-on individual contributor role with significant strategic impact. You’ll be responsible for architecting, building, and optimising real-time data infrastructure, collaborating closely with engineering, product, and analytics teams to ensure seamless data flow across the organisation. You’ll own the full data lifecycle—from ingestion to transformation and delivery—leveraging modern cloud and streaming technologies.
Responsibilities
- Design and build scalable, low-latency real-time data pipelines
- Integrate diverse data sources and ensure data accuracy and integrity
- Develop and maintain data models optimised for real-time querying
- Build fault-tolerant ingestion processes and ensure high availability
- Implement logging, monitoring, and alerting for infrastructure health
- Partner with cross-functional teams to deliver robust data solutions
What You’ll Bring
- Strong hands-on experience building streaming data platforms
- Deep understanding of tools like Kafka, Flink, Spark Streaming, etc.
- Proficiency in Python, Java, or Scala
- Cloud experience with AWS, GCP, or Azure
- Familiarity with orchestration tools like Airflow, Kubernetes
- Collaborative, solutions-focused mindset and a willingness to lead from the front
What’s on Offer
- Competitive base salary + quarterly bonus
- Hybrid working with a central London HQ
- Private healthcare
- Regular team socials, lunch clubs, and international company offsites
- Ongoing investment in training and development
- Opportunity to shape a new function and work on greenfield tech
Lead Data Engineer employer: Atarus
Contact Detail:
Atarus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Kafka, Flink, and Spark Streaming. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who have experience in building real-time data platforms. Engaging in discussions on platforms like LinkedIn or attending relevant meetups can provide insights and potentially lead to referrals.
✨Tip Number 3
Showcase your collaborative skills by preparing examples of past projects where you worked closely with cross-functional teams. Highlighting your ability to partner effectively with engineering, product, and analytics teams will demonstrate your fit for the role.
✨Tip Number 4
Stay updated on the latest trends and best practices in data engineering, particularly around cloud technologies like AWS, GCP, or Azure. Being knowledgeable about current advancements can help you discuss innovative solutions during interviews.
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 with real-time data platforms and relevant technologies like Kafka, Flink, and Spark Streaming. Use specific examples to demonstrate your hands-on experience and the impact you've had in previous roles.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills align with the responsibilities outlined in the job description, particularly your experience in building scalable data pipelines and collaborating with cross-functional teams.
Showcase Relevant Projects: If you have worked on projects that involved cloud technologies or orchestration tools like Airflow or Kubernetes, be sure to include these in your application. Highlight your contributions and the outcomes of these projects to demonstrate your expertise.
Proofread Your Application: Before submitting your application, take the time to proofread it for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial for a Lead Data Engineer role.
How to prepare for a job interview at Atarus
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with streaming data platforms and the specific tools mentioned in the job description, such as Kafka, Flink, and Spark Streaming. Consider bringing examples of past projects where you successfully built real-time data pipelines.
✨Demonstrate Your Problem-Solving Abilities
During the interview, highlight your collaborative approach to problem-solving. Share instances where you partnered with cross-functional teams to deliver robust data solutions, showcasing your ability to lead from the front.
✨Understand the Company’s Vision
Research the company’s growth trajectory and their investment in engineering and data functions. Being able to articulate how your skills align with their goals will demonstrate your genuine interest in the role and the organisation.
✨Prepare Questions for the Interviewers
Have a list of insightful questions ready to ask your interviewers. This could include inquiries about their current data infrastructure challenges or how they envision the new data platform evolving. It shows your enthusiasm and strategic thinking.
