Senior Data Platform Engineer: Data-as-Product & Self-Serve

DEPOP; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working options

Dog-friendly offices

Life Insurance

Pension matching

Free shipping on Depop

Job summary

Depop is seeking a Senior Data Platform (Enablement) Engineer to architect, build, and scale our data platform in London or remotely. You will empower teams to own, process, query and manage data with self-service capabilities.

You will work with data scientists, ML engineers, analytics engineers and other data teams to promote self-service tools, data governance, and robust pipelines using Databricks, Airflow and dbt.

Qualifications

• Experience with streaming ecosystems (Kafka, Flink, Confluent)
• Strong programming skills in Python or Scala
• Experience delivering data compliance & privacy solutions
• Experience with data governance, observability, data lineage
• Proven design/build of production-grade data platforms
• Experience with Airflow, dbt, Databricks and data observability/catalogue solutions
• Cloud familiarity: AWS, GCP, Azure
• Eagerness to learn and grow with dedicated time and resources

Responsibilities

• Pave data-as-a-product by introducing governance and observability tooling
• Develop microservices and data pipelines
• Design platform services enabling secure data access
• Lead initiatives with data scientists and ML engineers
• Uphold operational excellence with scalable services and incident response
• Collaborate with stakeholders to implement data solutions
• Mentor teammates and promote engineering standards
• Contribute to Depop's data culture and best practices

Skills

Streaming systems

Python

Scala

Data governance

Cloud platforms

Data products

Mentoring

Tools

Airflow

dbt

Databricks

Kafka

Terraform

Docker

Job description

Depop is seeking a Senior Data Platform (Enablement) Engineer to architect, build, and scale our data platform in London or remotely. You will empower teams to own, process, query and manage data with self-service capabilities.

You will work with data scientists, ML engineers, analytics engineers and other data teams to promote self-service tools, data governance, and robust pipelines using Databricks, Airflow and dbt.