Senior Data Engineer - Analytics Engineering in London

Depop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.

Founded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life.

Powered by a team of over 500 people, our company is headquartered in London, with offices in New York. In 2021, Depop became a wholly-owned subsidiary of Etsy and continues to operate as a standalone company.

We aim 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.

The Analytics Engineering team works across all data domains to support our internal partners in building high-quality, ready-to-use datasets. As a Senior Data Engineer, you'll play a pivotal role in shaping our data landscape, empowering teams across the organization with reliable, high-quality data. You'll contribute to a vibrant data culture, fostering self-service capabilities and driving impactful insights.

Responsibilities:

• Build and champion central data models that are used in Insights, ML and Search pipelines.
• Design and deliver robust and production ready 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.
• Contribute to the team’s vision and roadmap, and lead technically complex initiatives and be responsible for their success.
• Enhance our engineering efficiency by developing our internal tooling, CI/CD practices, and alerts/logging.
• Foster growth and capabilities in our less experienced engineers through coaching, and support our data consumers in building their own models.
• Cultivate a collaborative data culture that empowers self-serve data and model creation.

Qualifications:

• Consistent track record of successful end-to-end delivery of production ready 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.
• Strong stakeholder management and communications, including documentation, planning and delivery management.
• Passionate about sharing knowledge and mentoring less experienced engineers, fostering their growth and skill development.
• Strong programming skills in SQL and Python, with experience in services and platforms like Databricks, Airflow, dbt and Looker.
• Proficient with data engineering best practices, data warehousing and data design, including performance and cost optimisation, observability, governance and monitoring.
• Experience working with and integrating different parts of the data stack.
• You've leveraged 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.

Additional Information:

• Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa, subsidised counselling and coaching with Self Space, Cycle to Work scheme, Employee Assistance Programme (EAP) for 24/7 confidential support.
• Work/Life Balance: 25 days of annual leave with the option to carry over up to 5 days, impact hours, fully paid 4-week sabbatical after completion of 5 years of consecutive service.
• Flexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options.
• Family Life: 20 weeks of paid parental leave for full-time regular employees for birth parents, 12 weeks for non-birth parents, IVF leave, shared parental leave, and paid emergency parent/carer leave.
• Learn + Grow: Twice-yearly development chats and yearly performance reviews, learning budget, upskilling our employees with company-wide training workshops.
• Your Future: Life Insurance (financial compensation of 3x your salary), pension matching up to 6% of full base salary with Aviva.
• Depop Extras: In-office Depop Shop and a packing station with free delivery.