20 days ago
Remote, United Kingdom or London, United KingdomSenior
Responsibilities
- Architect, build, and scale self-service data platform capabilities and data-as-a-product practices.
- Develop microservices, libraries, data pipelines, and platform services using modern cloud-native patterns.
- Own data transformation and orchestration tooling, batch and streaming infrastructure, exploration tools, and data lake capabilities.
- Introduce data governance, observability, lineage, data contracts, SLA/SLO tracking, tagging, privacy controls, and data quality monitoring.
- Lead technical initiatives supporting data scientists, ML engineers, analytics engineers, product engineers, and other data users.
- Build scalable services, participate in incident response and root cause analysis, and improve platform health and performance.
- Automate best practices and support documentation, tutorials, training sessions, mentoring, and knowledge sharing.
- Collaborate with technical and non-technical stakeholders to define, design, and implement Data Platform solutions.
- Contribute to Depop’s engineering culture and continuous improvement efforts.
Requirements
- Experience with Kafka, Flink, Confluent, or another streaming ecosystem and a solid understanding of its components.
- Advanced proficiency in a high-level programming language such as Python or Scala, with strong software engineering practices.
- Experience delivering data compliance and privacy solutions that uphold customer data subject rights.
- Experience implementing data governance and observability capabilities including lineage, data contracts, SLA/SLOs, tagging, and data quality monitoring.
- Proven experience designing, building, and scaling data platforms and backend infrastructure in production environments.
- Expertise with big data and data platform tools such as Airflow, dbt, Kafka, Databricks, and data observability or catalog solutions such as Monte Carlo, Atlan, or DataHub.
- Cloud platform proficiency with AWS, GCP, or Microsoft Azure and hands-on experience building scalable, reliable cloud data solutions.
- Preferred knowledge of systems design in modern cloud-based environments.
- Preferred advanced experience with at least one data lake table or file format: Delta Lake, Parquet, Iceberg, or Hudi.
- Preferred experience with lakehouse or medallion architectures in Databricks.
- Preferred experience with experimentation support tooling such as Optimizely.
- Curiosity about AI and willingness to explore how it can improve day-to-day work.
Benefits
- PMI and cash plan healthcare access with Bupa, subsidised counselling and coaching with Self Space, an Employee Assistance Programme, and Mental Health First Aiders.
- Cycle to Work scheme with Evans or the Green Commute Initiative.
- 25 days of annual leave, with the option to carry over up to 5 days, plus up to 2 additional paid volunteering days annually.
- A fully paid 4-week sabbatical after 5 years of consecutive service.
- Flexible MyMode hybrid working with flex, office-based, and remote options depending on the role; offices are dog-friendly.
- Paid parental leave, IVF leave, shared parental leave, and paid emergency parent or carer leave.
- Twice-yearly development chats, yearly performance reviews, a learning budget, and company-wide training resources.
- Life insurance at 3 times salary and pension matching up to 6% of full base salary with Aviva.
- Free in-office Depop Shop, packing station with free delivery, and milestone gifts and rewards.
Tech Stack
Apache AirflowApache FlinkApache KafkaAWSAzureDatabricksdbtDockerGoogle Cloud PlatformPythonScalaTerraform
Categories
BackendData Engineering
