Staff Data Engineer

Staff Data Engineer

London Full-Time 43200 - 72000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the evolution of our data platform and support diverse data use cases.
  • Company: Join one of Europe's largest media companies, where data drives innovation.
  • Benefits: Enjoy flexible working options, a collaborative culture, and opportunities for professional growth.
  • Why this job: Be at the forefront of data-driven decision-making and work with unique datasets.
  • Qualifications: Proven experience in data engineering, Python, and modern data architectures required.
  • Other info: Opportunity to coach and mentor fellow engineers while shaping the future of data.

The predicted salary is between 43200 - 72000 ÂŁ per year.

Accepting applications until: 30 May 2025 Job Description

Staff Data Engineer

Your Role: Staff Data Engineer

We’re one of the largest media players in Europe, and data is at the heart of what we do. We capture data from our audio and digital channels, from our extensive outdoor business and beyond, and use this to create the best content for our audiences and an amazing experience for our clients.

The data team supports the whole company across all of these areas, and this scope gives us a rich array of data use cases to work on. These range from personalisation on our digital applications, to optimisation algorithms to allocate our inventory, to data for enabling operational excellence in our outdoor estate, generative technologies to develop ad creatives, and many others.

Three things set us apart:

  1. Distinctive problems to solve: As described above, we have some of the most diverse and rich data use cases for any media company. We’re the only player to cut across audio, outdoor, digital, and to run a programmatic ad exchange.

  2. Unique data sets: In line with the above, we have some truly unique data sets to work with – and at large scale. This includes our front-end data, data from our ad exchange, outdoor operational data, audio listening data, and much more. It also includes some unique data partnerships: for example, we have access to unique data on travel movements for the TfL network in London.

  3. Scale: We’re a privately-owned, mid-cap business, with a long-term perspective. We have the flexibility, pace, and opportunity to work on big problems that an early-stage business would. But equally, we have the scale to make an impact on millions of consumers, and the big data volumes you’d expect of a large business.

We’re looking for a Staff Data Engineer to play a central role in the evolution of our Data Platform and its application for use cases across the company. It is a unique opportunity to continue the work to develop and maintain a robust data infrastructure that supports the organisation’s data-driven initiatives across Global’s multiple data products.

Key Responsibilities

This position requires someone to have a deep understanding of data architecture and engineering best practices, as well as a track record of successfully building data platforms.

  1. Technical Leadership (20%): Being highly skilled and possessing deep technical knowledge, you will provide technical leadership and guidance to the engineering team, helping to shape the overall technical direction of projects.

  2. Design and architecture (20%): We’re continually looking to evolve our data platform, and to consider application to new use cases – including personalisation, generative AI technology in ad creation, low latency programmatic advertising, and many others. You’ll contribute to the design and architecture of our data platform with a focus on the long term, bringing a strong understanding of software design principles, scalability, and performance considerations.

  3. Owning and improving our data infrastructure (20%): You’ll need to go beyond the architectural vision alone and support our work in building our data platform for the future. You’ll be capable of being hands-on and contributing to our delivery.

  4. Technical Documentation (10%): Documenting technical designs, system architectures, and coding standards to facilitate knowledge sharing and maintain a high level of technical documentation.

  5. Obsessing over quality (10%): You’ll know that “garbage in” can mean “garbage out” in data. We’d expect you to strive for high standards of data quality, and to ensure our platforms are built to a high standard as well. You will drive engineering excellence across the team setting and ensuring adherence to coding standards, best practices, and quality guidelines.

  6. Coaching and supporting others (20%): While this is not a people management role, you’ll be a senior technical leader in the team. As such, we’d look for you to coach and guide the engineers who you work closely with.

What You’ll Love About This Role

Think Big: You’ll be at the heart of designing how we evolve our data platform, which will underpin critical business decisions and insights for Global’s future.

Own It: You’ll be doing this by leading technical delivery on some of our most important use cases.

Keep it Simple: We’ve got some of the largest and most diverse data sets in UK media – with scale that continues to grow. You’ll play a leading role in how we enable our platforms to meet this scaling challenge while remaining reliable, maintainable, and cost-effective.

Better Together: You’ll be part of a diverse data team, and have an opportunity to work alongside highly talented engineers, data scientists, and data analysts to deliver our most important business outcomes.

What Success Looks Like

In your first few months, you’ll have:

  1. Acquired a deep understanding of our data platform, its architecture, engineering challenges, work methodologies, and the use cases it can support.

  2. Fostered an active and collaborative way of working within the team, demonstrating effective leadership and support for others.

  3. Learned about use cases for our data platform, and found opportunities to evolve it for the future.

  4. Shown passion to research and apply the latest data tools and techniques in the market.

What You’ll Need

The ideal candidate will be proactive and willing to develop and implement innovative solutions, capable of the following:

  1. An excellent applied understanding of modern data architectures (using Snowflake & dbt ) with real-world experience of running them in production at scale both for batch and streaming data flows.

  2. Extensive data engineering experience using Python both for data pipelines and application development.

  3. Proficiency with cloud services (ideally AWS).

  4. Experience setting up a robust SDLC (software delivery lifecycle) including use of automated testing & CI/CD (i.e. Github Actions, Jenkins).

  5. A strong desire to work smarter using repeatable patterns to drive automation and engineering efficiency.

  6. A strategic approach to problem solving and the ability to see the big picture at all times.

  7. Good communication skills, demonstrated in the design of solutions and technical decisions, being able to bridge the gap with non-technical partners and sharing knowledge with less experienced engineers.

  8. Ability to influence long term roadmap, by advocating for technical investments and building future-proof solutions.

  9. A track record of developing other team members by coaching them to improve their skills and raising the bar by demonstrating quality & best practices in your own work.

Bonus Points for:

  1. AWS/Azure/GCP Certifications.

  2. Experience with Infrastructure as Code (e.g. Terraform).

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Staff Data Engineer employer: Global

As a leading media player in Europe, we offer an exceptional work environment for our Staff Data Engineers, characterised by a culture of innovation and collaboration. Our diverse data use cases and unique datasets provide unparalleled opportunities for professional growth and technical leadership, while our commitment to quality ensures that you will be part of a team dedicated to excellence. With the flexibility of a mid-cap business and the impact of a large organisation, you'll find meaningful challenges that drive your career forward in a dynamic and supportive atmosphere.
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Contact Detail:

Global Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Data Engineer

✨Tip Number 1

Familiarise yourself with the specific technologies mentioned in the job description, such as Snowflake, dbt, and Python. Having hands-on experience or projects that showcase your skills with these tools will make you stand out during discussions.

✨Tip Number 2

Network with current employees or professionals in similar roles within the media industry. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals, which can significantly boost your chances of landing the job.

✨Tip Number 3

Prepare to discuss your approach to problem-solving and how you've implemented innovative solutions in past roles. Be ready to share specific examples that demonstrate your strategic thinking and ability to see the big picture, as this aligns with what they are looking for.

✨Tip Number 4

Showcase your leadership skills by discussing any mentoring or coaching experiences you've had. Highlighting your ability to guide less experienced engineers will resonate well, as the role requires a senior technical leader who can support and uplift the team.

We think you need these skills to ace Staff Data Engineer

Data Architecture
Data Engineering Best Practices
Technical Leadership
Software Design Principles
Scalability and Performance Considerations
Hands-on Data Platform Development
Technical Documentation
Data Quality Assurance
Coding Standards Adherence
Coaching and Mentoring
Modern Data Architectures (Snowflake & dbt)
Python for Data Pipelines and Application Development
Cloud Services Proficiency (AWS preferred)
Software Delivery Lifecycle (SDLC) Management
Automated Testing and CI/CD (e.g. Github Actions, Jenkins)
Automation and Engineering Efficiency
Strategic Problem Solving
Effective Communication Skills
Influencing Technical Roadmaps
Team Development and Coaching

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with modern data architectures like Snowflake and dbt. Emphasise your proficiency in Python and cloud services, as these are key requirements for the role.

Craft a Compelling Cover Letter: In your cover letter, express your passion for data and how your skills align with the company's mission. Mention specific projects or experiences that demonstrate your ability to solve complex data problems and your leadership in technical delivery.

Showcase Technical Skills: Include a section in your application that details your technical skills, especially those related to data pipelines, automated testing, and CI/CD processes. Highlight any experience you have with AWS or other cloud services, as well as any relevant certifications.

Demonstrate Problem-Solving Ability: Provide examples in your application of how you've approached and solved data-related challenges in previous roles. This could include specific use cases where you improved data quality or optimised data infrastructure.

How to prepare for a job interview at Global

✨Showcase Your Technical Expertise

Be prepared to discuss your experience with modern data architectures, particularly with tools like Snowflake and dbt. Highlight specific projects where you've successfully implemented these technologies in production environments.

✨Demonstrate Problem-Solving Skills

Expect questions that assess your strategic approach to problem-solving. Prepare examples of how you've tackled complex data engineering challenges and the innovative solutions you've implemented.

✨Communicate Effectively

Since you'll need to bridge the gap between technical and non-technical partners, practice explaining your technical decisions in simple terms. This will show your ability to collaborate across teams.

✨Emphasise Coaching and Leadership

Even though this isn't a people management role, be ready to discuss how you've coached or mentored other engineers. Share examples of how you've helped others improve their skills and adhere to best practices.

Staff Data Engineer
Global
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