Senior Data Platform Engineer - Data Enablement
Depop · London, United Kingdom ·
- Seniority
- Senior
- Employment
- Full time
- Category
- Data engineering
- Experience
- 5+ years
- Company size
- 501-1000
Depop · London, United Kingdom ·
Depop Limited - Nova · London, United Kingdom
etsy · Depop - Remote, UK
etsy · London, UK
etsy · London, UK
Depop is hiring a Senior Data Platform (Enablement) Engineer in London to architect, build, and scale its data platform so teams can self-serve their data needs. Day to day this means owning transformation and orchestration tooling, batch and streaming infrastructure, and the data lake, using Kafka, Databricks, Airflow, dbt, Terraform, Docker, and cloud platforms.
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. We believe that everything you want already exists, and our role is to help people discover it.
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 - the global marketplace for unique and creative goods - and continues to operate as a standalone company. For more information, visit www.depop.com
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. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.
We use AI tools (Google Gemini) to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters in identifying great talent but do not replace human decision‑making. At Depop, every hiring decision is made by a human.
If, due to a disability, you need adjustments to complete the application, please let us know by sending an email with your name, the role to which you would like to apply, and the type of support you need to complete the application to [email protected].
Depop is looking for a Senior Data Platform (Enablement) Engineer to help architect, build, and scale our data platform, empowering teams with self‑serve capabilities. You’ll combine hands‑on technical expertise with strategic thinking to shape the foundation that supports our products and customers, enabling teams own, process, query, and manage their data with efficiency and ease.
You will work closely with people from a wide variety of domains: Product Data Scientists, Analytics Engineers, ML Engineers, MLOps, MarTech and other Data Engineering teams. You will help manage our growing data needs and support increasingly complex business problems by building and promoting self‑service tools and data best practices that will be used across the organisation, including taking ownership of our data transformation and orchestration tooling; batch and streaming infrastructure and exploration tools (Databricks, Airflow, dbt) and look after our Datalake (ingestion, storage, governance, privacy).
You’ll work with a modern, cutting‑edge data stack and play a key role in shaping data‑as‑a‑product practices. As we scale to meet Depop’s bold growth ambitions, you’ll help introduce the next generation of data capabilities.
Want to find out more about Depop & our engineering team?
We write about technology, people and smart engineering right here - https://engineering.depop.com/
Pave a path for data as product: Champion data as a first-class citizen by introducing robust data observability and governance tooling into the platform
Software engineering: Develop microservices, libraries, data pipelines
Technical design: implement and evolve platform services that enable teams to work with data efficiently and securely, using modern tooling such as Kafka, Terraform, Docker, and cloud-native patterns
Lead technical initiatives: Lead initiatives working with end users: data scientists, ML engineers, analytics engineers, product engineers and beyond to enable, support and accelerate their data needs, embracing a platform as product mindset
Uphold operational excellence: building scalable services, leading incident response and root cause analysis, and continuously improving the health and performance of our data platform. Champion scalable best practices through automation, clear documentation, and knowledge sharing via tutorials and training sessions
Stakeholder collaboration: Work closely with both technical and non-technical stakeholders to define, design, and implement solutions within our Data Platform. Trusted relationship will be key for success
Invest in others’ growth: Mentoring and sharing knowledge, helping elevate technical standards and fostering a culture of continuous improvement
Build on engineering culture You take an active role in improving the engineering culture at Depop and encourage others around you to follow these values
Streaming knowledge: Experience with Kafka/Flink/Confluent or other streaming ecosystems, with a solid understanding of their components
Advanced knowledge in a high-level programming language (e.g. Python, Scala) with solid foundation in software engineering best practices - testing, clean coding standards, code reviews, pair programming, automation-first mindset
Experience delivering data compliance & privacy solutions, ensuring that we uphold data subject rights for our customers
Experience introducing a data governance & observability stack enabling rich data lineage, data contracts, SLA/SLO, tagging and data quality monitoring capabilities both on our own platform but also for data owners
Proven experience designing, building, and scaling data platforms and backend infrastructure in production environments - have worked to enable advanced data users: ML Engineers, analysts, analytics engineers and have a strong grasp of their needs and how they operate
Big data technologies, with expertise in tools & platforms such as Airflow, dbt, Kafka, Databricks and data observability & catalogue) solutions (e.g. Monte Carlo, Atlan, Datahub)
Cloud Platform proficiency: familiarity with AWS, GCP, or Microsoft Azure, with hands‑on experience building scalable, reliable data solutions on cloud platforms
A passion for learning new things and keeping on top of the latest developments and technologies in our field. We take pride in our learning and make sure to have dedicated time set aside for our growth and development (we offer personal development time and other platforms to share knowledge with your peers)
Knowledge of systems design within a modern cloud-based environment
Advanced experience working and understanding the tradeoffs of at least one of the following Data Lake table/file formats: Delta Lake, Parquet, Iceberg, Hudi
Experience working with lakehouse / medallion architectures in Databricks
Experience with experimentation support tooling (such as Optimizely)
A genuine curiosity about AI and a willingness to explore how it can enhance your day-to-day work
etsy · Depop - Remote, UK