IT & Software

Senior BigQuery Data Engineer

Checkout.com

London · Greater London · United Kingdom

Overview

In this role, you will help build and scale Checkout.com’s data platform to power products and analytics. You’ll enable internal teams to publish data and deploy streaming applications, solving business problems with a scalable event-driven foundation. You’ll mentor juniors, drive best practices across squads, and uphold data quality and governance. This role combines hands-on engineering with shaping how the company leverages data at scale to impact product and business decisions.

Pay / Benefits
  • hybrid working model
  • three days in the office
  • ownership and impact
  • growth opportunities
  • collaboration culture
  • recognition for impact
Responsibilities
  • Build and operate a large-scale event streaming platform using Kafka, kSQL, and Flink
  • Automate workflows to make the platform self-sustaining
  • Stay abreast of data and streaming tech trends and share knowledge
  • Mentor junior engineers and collaborate with application teams for best practices
  • Develop tooling (SDKs/DSLs) and documentation to enable upstream data publishing and streaming app deployment
  • Describe infrastructure as code (Terraform or similar) and design CI/CD pipelines
  • Provide consultancy to drive platform adoption and unlock use-cases
  • Champion data quality and governance as a core platform capability
  • Offer hands-on support for event-based systems including incident triage and root-cause analysis
Key requirements
  • Strong engineering background with ownership of data platform components
  • Experience with stream technologies (Kafka preferred; other like Kinesis acceptable)
  • Experience designing and implementing stream processing applications (kStreams, kSQL, Flink, Spark Streaming)
  • Experience with data warehousing tools such as BigQuery or Databricks and building pipelines on them
  • Experience with modern cloud stacks (AWS, Azure or GCP)
  • Excellent programming skills in Python, Java, Scala or C#
  • Mentorship and collaboration abilities
  • Willingness to drive best practices across teams and organizations
  • Thought leadership evidenced by articles, podcasts, meetups or conference talks (preferred)
  • Mentorship
  • Collaboration
  • Active listening
  • Kafka (or Kinesis)
  • kSQL
  • Flink

Reference: WJ-747_30133754

Apply now

Continue on the employer's official application - the same link they use for every candidate.

More jobs

This role is listed on GigBlows for discovery and search. Hiring decisions and applications are handled by the employer or their chosen application system.