Data Platform Engineer: Real-Time Streaming & Kafka (Hybrid)

Depop Limited - Nova; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Health and wellbeing package

Cycle to work

Employee assistance programme

Life insurance

Pension matching

Hybrid/remote options

Job summary

Depop is hiring a Data Engineer to join the Data Platform team. You’ll own streaming pipelines, Kafka Connect, and the bronze layer, partnering with Data Infrastructure and Analytics Engineering.

You’ll help ensure data quality, latency vs completeness, and contribute to design discussions while collaborating with ML Insights. The role offers a hybrid working model with role-dependent remote options.

Qualifications

• Some experience building and operating production data pipelines, ideally including Kafka or another streaming/event-driven system.
• Working knowledge of at least one of Scala, Kotlin or Python, and willingness to work across all three as the team requires.
• Familiarity with data warehousing concepts (e.g. medallion architecture bronze/silver/gold) and an interest in data quality and freshness monitoring.
• Comfortable working with Kafka Connect, schema registries, and distributed systems concepts, or keen to build that experience quickly.
• A collaborative approach — this team works closely with Data Infrastructure, ML and Insights, and pairs regularly with senior engineers.

Responsibilities

• Build and maintain services in our Kafka Connect and streaming pipeline, including the kafka-forwarder and changelogs-processor, under the guidance of senior engineers.
• Contribute to extending the bronze streaming layer across Depop's growing table catalogue, working from well-scoped tickets through to production rollout.
• Help implement data contracts and freshness checks on streaming datasets, and build the quarantine/alerting that keeps bad data out of downstream consumers.
• Take part in the team's support rota, helping other teams onboard new events and troubleshoot streaming issues.
• Write clear documentation and contribute to design discussions, growing your judgement on trade-offs like latency vs completeness and cost vs freshness.
• Pair with senior engineers on more complex pieces of the streaming framework work, building towards owning larger pieces of it yourself.

Skills

Kafka

Streaming

Scala

Kotlin

Python

Data warehousing

Kafka Connect

Schema registries

Distributed systems

Collaborative

Tools

Kafka

Kafka Connect

Schema Registries

Scala

Kotlin

Python

Job description

Depop is hiring a Data Engineer to join the Data Platform team. You’ll own streaming pipelines, Kafka Connect, and the bronze layer, partnering with Data Infrastructure and Analytics Engineering.

You’ll help ensure data quality, latency vs completeness, and contribute to design discussions while collaborating with ML Insights. The role offers a hybrid working model with role-dependent remote options.