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- Tasks: Craft and optimise data pipelines to empower teams with high-quality insights.
- Company: Join Depop, a vibrant community-driven fashion marketplace redefining sustainability.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact in the circular fashion movement while developing your data engineering skills.
- Qualifications: Strong SQL and Python skills, with experience in data engineering tools and methodologies.
- Other info: Be part of a diverse team that values innovation and collaboration.
The predicted salary is between 48000 - 72000 £ per year.
Depop is the community-powered circular fashion marketplace where anyone can buy, sell and discover desirable secondhand fashion. With a community of over 35 million users, Depop is on a mission to make fashion circular, redefining fashion consumption. Founded in 2011, the company is headquartered in London, with offices in New York and Manchester, and in 2021 became a wholly-owned subsidiary of Etsy.
Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome, no matter who they are or where they’re from. Just as our platform connects people globally, we believe our workplace should reflect the diversity of the communities we serve. We thrive on the power of different perspectives and experiences, knowing they drive innovation and bring us closer to our users. We’re proud to be an equal opportunity employer, providing employment opportunities without regard to age, ethnicity, religion or belief, gender identity, sex, sexual orientation, disability, pregnancy or maternity, marriage and civil partnership, or any other protected status. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.
Responsibilities:
- Build and champion central data models that are used in Insights, ML and Search pipelines.
- Design and deliver robust data pipelines that deliver high-quality data for partner teams, such as insights, finance, ML, and operations.
- Build data models using our data stack, including Databricks, AWS, dbt, Airflow and Looker.
- Lead technical initiatives and be responsible for their success.
- Improve our engineering efficiency by developing our internal tooling, CI/CD practices, and alerts/logging.
- Foster growth and capabilities in our junior engineers through mentoring, and support our data consumers in building their own models.
- Cultivate a collaborative data culture that empowers self-serve data and model creation.
Requirements:
- Consistent track record of successful end-to-end delivery of projects; from partnering with business teams, scoping requirements, to implementation and maintenance.
- Experience aligning analytics engineering initiatives to a broader vision and to business objectives.
- Good stakeholder management and communications, including documentation, planning and delivery management.
- Strong programming skills in SQL and Python, with experience in services like Airflow, dbt and Looker.
- Proficient with data engineering methodologies, data warehousing and data design, including performance and cost optimisation, observability and monitoring.
- Experience working with and integrating different parts of the data stack.
- You’ve used BI tools, such as Looker, in a platform engineering capacity, helping to enable data scientists to build data models and self-serve analytics to business consumers.
- Experience developing CI/CD pipelines using Github Actions or Jenkins.
- Experience using Terraform.
Senior Data Engineer in London employer: Depop
Contact Detail:
Depop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Depop on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and Python skills. Be ready to showcase your experience with data pipelines and tools like Airflow and dbt. We want to see how you can make an impact!
✨Tip Number 3
Show off your collaborative spirit! During interviews, share examples of how you've worked with teams to deliver projects. Highlight your mentoring experiences too; we love seeing growth in others!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our community at Depop.
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with SQL, Python, and any relevant tools like Airflow and dbt. We want to see how your skills align with our mission at Depop!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for circular fashion and how you can contribute to our data culture. Let us know why you're excited about joining Depop and how you can help us empower our community.
Showcase Your Projects: If you've worked on any relevant projects, make sure to showcase them! Whether it's building data pipelines or developing CI/CD practices, we love seeing real examples of your work that demonstrate your capabilities.
Apply Through Our Website: We encourage you to apply through our website for the best experience. It helps us keep track of your application and ensures you get all the updates. Plus, it’s super easy to do!
How to prepare for a job interview at Depop
✨Know Your Data Stack
Make sure you’re well-versed in the tools mentioned in the job description, like Databricks, AWS, dbt, Airflow, and Looker. Brush up on how these tools integrate with each other and be ready to discuss your experience using them in real projects.
✨Showcase Your Project Success
Prepare to talk about specific projects where you’ve successfully delivered end-to-end data solutions. Highlight your role in scoping requirements, implementation, and how you maintained those projects over time. Use metrics to demonstrate the impact of your work.
✨Communicate Clearly
Since stakeholder management is key, practice explaining complex technical concepts in simple terms. Be ready to discuss how you’ve collaborated with non-technical teams and how you document your processes to ensure everyone is on the same page.
✨Mentorship Matters
If you have experience mentoring junior engineers, be prepared to share examples of how you’ve fostered their growth. Discuss your approach to building a collaborative culture and how you empower others to create their own data models.
