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- Tasks: Lead the design and implementation of scalable data systems and architecture.
- Company: Join Net Talent, a leading recruitment firm in IT, Data, AI, and Digital sectors.
- Benefits: Enjoy hybrid work options and a collaborative team environment.
- Why this job: Make a real impact by solving complex challenges and mentoring fellow engineers.
- Qualifications: 8+ years in data engineering with expertise in modern tools like Spark and AWS.
- Other info: This is a mid-senior level full-time role based in Central belt Scotland.
The predicted salary is between 43200 - 72000 ÂŁ per year.
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CEO and founder of Net Talent and People TalentExecutive SearchIT, Data, AI, Digital and HR RecruiterTalent PartnerCIPD/Associate
Location: Central belt Scotland – Hybrid 3 days on site
We working exclusively on an exciting opportunity for a Staff Data Engineer to lead the technical design and implementation of our most critical data infrastructure and products. In this senior-level individual contributor role, you’ll be responsible for designing scalable systems, setting data architecture standards, and solving complex technical challenges that power analytics, data science, and business functions across the company.
You’ll collaborate with engineers, product managers, and business stakeholders to architect performant, reliable, and long-term data solutions that are customer-centric and business-aligned.
What You’ll Do:
- Design and build scalable, reliable, and high-performance data systems.
- Define and drive best practices for data modeling, ETL/ELT pipelines, and real-time streaming architectures.
- Set technical direction and architectural standards across the data platform.
- Work closely with cross-functional partners to meet evolving business and analytical needs.
- Own complex technical systems end-to-end, from concept to production.
- Advocate for engineering excellence and mentor other engineers on the team.
Technical Skills:
- 8+ years of experience in data engineering or a related field, with a focus on building scalable data systems and platforms.
- Strong expertise with modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure).
- Deep understanding of data modeling, distributed systems, streaming architectures, and ETL/ELT pipelines.
- Proficiency in SQL and at least one programming language such as Python, Scala, or Java.
- Demonstrated experience owning and delivering complex systems from architecture through implementation.
- Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
Preferred Qualifications:
- Experience designing data platforms that support analytics, machine learning, and real-time operational workloads.
- Familiarity with data governance, privacy, and compliance frameworks (e.g., GDPR, HIPAA).
- Background in customer-centric or product-driven industries such as digital, eCommerce, or SaaS.
- Experience with infrastructure-as-code tools like Terraform and expertise in data observability and monitoring practices.
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Information Technology
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Industries
Software Development
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Senior Data Engineer employer: Net Talent
Contact Detail:
Net Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network with professionals in the data engineering field, especially those who work with the tools and frameworks mentioned in the job description. Engaging with them on platforms like LinkedIn can provide insights into the company culture and expectations.
✨Tip Number 2
Familiarise yourself with the latest trends in data architecture and scalable systems. Being able to discuss recent advancements or case studies during your conversations can demonstrate your passion and expertise in the field.
✨Tip Number 3
Prepare to showcase your experience with complex technical systems. Think of specific projects where you’ve led the design and implementation, and be ready to discuss the challenges you faced and how you overcame them.
✨Tip Number 4
Since this role involves collaboration with cross-functional teams, practice articulating technical concepts in a way that non-technical stakeholders can understand. This skill is crucial and can set you apart from other candidates.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, particularly with scalable systems and the specific tools mentioned in the job description, such as Spark, dbt, and Airflow. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about data engineering and how your skills align with the company's needs. Mention specific projects where you've designed or implemented data solutions, showcasing your problem-solving abilities.
Showcase Technical Skills: Include a section in your CV that lists your technical skills prominently. Highlight your proficiency in SQL and programming languages like Python or Scala, as well as your experience with cloud services like AWS or GCP.
Prepare for Technical Questions: Anticipate technical questions related to data architecture and engineering practices. Be ready to discuss your previous projects in detail, focusing on your role in designing and implementing complex systems.
How to prepare for a job interview at Net Talent
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with modern data tools and frameworks like Spark, dbt, and Kafka. Highlight specific projects where you designed scalable data systems and explain the technical challenges you faced and how you overcame them.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will demonstrate your ability to bridge the gap between different teams and ensure everyone is on the same page.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills. Prepare to discuss how you would approach designing a data architecture for a specific business need or how you would handle a data pipeline failure. Use real-life examples from your past experiences.
✨Emphasise Collaboration and Mentorship
As a senior data engineer, you'll be expected to mentor others. Share examples of how you've collaborated with cross-functional teams and mentored junior engineers. This shows your leadership potential and commitment to engineering excellence.
