At a Glance
- Tasks: Lead the Central Data Engineering team to build large-scale data pipelines and support AI projects.
- Company: Join Spotify, a revolutionary audio streaming service with a passion for creativity.
- Benefits: Flexible remote work, competitive salary, and a culture of inclusivity and growth.
- Other info: Dynamic environment with opportunities for mentorship and career advancement.
- Why this job: Make an impact on innovative AI experiences while collaborating with diverse teams.
- Qualifications: Experience in Data Engineering, Python programming, and building high-quality datasets.
As a Senior Data Engineer in our new Central Data Engineering team in the Platform Mission, you will be leading work that is mission-wide in terms of scope. Our new Central Data Engineering team will inform data quality standards, access standards, create templatised solutions, assist in managing mission-level datasets/dashboards, and prepare our mission’s data for the AI Future that is expected to impact every squad and product area.
As the Senior engineer on the team, you will deal with bringing structure to ambiguity and be the bridge between business goals and translating them to technical deliverables.
What you'll do:
- Build large-scale data pipelines using frameworks like Google Cloud Platform and Apache Beam.
- Work on projects powering new generative AI experiences and helping to build models.
- Learn and contribute to the team's best practices and techniques for building data pipelines for large-scale models, including cleaning, filtering, classifying, and labeling.
- Collaborate with other engineers, researchers, product managers, and stakeholders, taking on learning and leadership opportunities that arise.
- Deliver scalable, testable, maintainable, and high-quality code.
- Share knowledge, promote standard methodologies, and improve the team through mentorship and constructive accountability.
Who you are:
- You have Data Engineering experience and know how to work with high-volume, heterogeneous data, preferably with distributed systems such as Hadoop, BigTable, Cassandra, GCP, AWS.
- You have experience building clean, high-quality datasets for training large-scale models.
- You have experience with one or more higher-level Python or Java-based data processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark, etc.
- You have strong Python programming abilities.
- You might have worked with Docker as well as Luigi, Airflow, or similar tools.
- You care about quality and know what it means to ship high-quality code.
- You have experience managing data retention policies.
- You care about agile software processes, data-driven development, reliability, and responsible experimentation.
- You understand the value of collaboration and partnership within teams.
Where you’ll be:
This role is based in London. We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Remote Senior Data Engineer - Platform Engineering in Essex employer: Spotify
At Spotify, we pride ourselves on being an exceptional employer, offering a dynamic work culture that champions inclusivity and collaboration. As a Senior Data Engineer in our London-based Central Data Engineering team, you'll have the opportunity to lead innovative projects while enjoying the flexibility of remote work. We are committed to your professional growth, providing mentorship and learning opportunities that empower you to thrive in a fast-paced, data-driven environment.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Data Engineer - Platform Engineering in Essex
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already at Spotify. A friendly chat can open doors and give you insider info on what it’s really like to work there.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects that highlight your data engineering prowess, make sure to share it. It’s a great way to demonstrate your experience with frameworks like GCP and Apache Beam.
✨Tip Number 3
Prepare for the interview by brushing up on your Python and data pipeline knowledge. Be ready to discuss how you’ve tackled ambiguity in past projects and how you can bridge business goals with technical solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Remote Senior Data Engineer - Platform Engineering in Essex
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Data Engineer role. Highlight your experience with data pipelines, frameworks like GCP and Apache Beam, and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our mission. Share specific examples of your work that demonstrate your ability to bridge business goals with technical deliverables.
Showcase Your Technical Skills:Don’t forget to mention your programming prowess, especially in Python or Java. If you've worked with tools like Docker, Airflow, or similar, make sure to include that too. We want to see your technical side shine!
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’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Spotify
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering skills, especially with frameworks like Google Cloud Platform and Apache Beam. Be ready to discuss your experience with high-volume data and distributed systems, as this will show that you understand the technical requirements of the role.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled ambiguity in past projects. The interviewers will want to see how you can bridge business goals with technical deliverables, so think of specific instances where you've successfully navigated challenges.
✨Collaborate Like a Pro
Since this role involves working closely with engineers, researchers, and product managers, be prepared to talk about your collaborative experiences. Highlight any leadership roles you've taken on and how you've contributed to team success through mentorship or knowledge sharing.
✨Quality Over Everything
Emphasise your commitment to delivering high-quality code. Discuss your experience with testing and maintaining scalable data pipelines, and be ready to explain how you ensure data quality and reliability in your work.