Senior Data Engineer with DevOps
About the role
Our client is one of the largest game studios known for their very successful MOBA and FPS franchises. You will be a member of the Data Operations team focused on modernizing the Analytics Platform and building the services, tooling, and infrastructure that support data ingestion, schema management, and reliable delivery of analytics data into Databricks.
As a core contributor, you will play a vital role in building dependable data solutions capable of processing petabytes of information. Your work will span backend services, schema and metadata tooling, cloud infrastructure, CI/CD, and production operations. You will help product teams and internal platform users adopt new data standards, migrate safely from legacy systems, and operate their services with improved reliability, observability, and efficiency.
You will bring your experience working with large-scale data systems and production infrastructure to help design and operate a modern data platform that is easier to evolve, safer to change, and better aligned with future data engineering needs.
Responsibilities
Design, build, and operate services and pipelines that power analytics data ingestion, schema management, and delivery into Databricks
Modernize legacy platform components by migrating services, libraries, and deployment workflows to modern Java and application standards
Build automation, CI/CD flows, and scenario/integration test coverage to make platform changes safe and repeatable
Design and maintain production infrastructure in AWS using Infrastructure as Code tooling such as Terraform
Improve data quality through stronger schema validation, metadata capture, lineage tracking, and operational guardrails
Build tooling and paved paths that help internal customers migrate to new ingestion and schema standards
Collaborate with cross-functional teams to prepare design docs, rollout plans, and implementation strategies for platform changes
Monitor live systems, investigate incidents, and be part of the on-call team that provides 3rd line support to live analytics services
Support performance, reliability, and cost optimization across ingestion and processing flows
Required qualifications
Minimum of 5 years commercial work experience in software engineering, data engineering, platform engineering, or a related field
Bachelor's or higher degree in Computer Science, Software Engineering, or a related field
Coding skills, with commercial experience in one of the following languages - Java, Python, Golang
Knowledge in Infrastructure as Code tooling, e.g. Terraform
Experience with CI/CD tooling, e.g. GitHub Actions, Jenkins, Docker
Experience with streaming and schema-driven systems, e.g. Kafka, Protobuf, JSON Schema, or schema registries
Commercial experience with Airflow and DBT (Data Build Tool)
Commercial experience with Databricks
Commercial experience with Spark /PySpark
Effective communication and teamwork skills
Nice to have
Experience migrating legacy services or frameworks to modern application stacks
Experience with Databricks
Delta Live Tables andUnity Catalog
Experience with AWS, especially Kafka /MSK-based data flows, S3, IAM and VPC /networking.
Experience with Buf, Protobuf tooling, or JSON-to-Protobuf migration work
Familiarity with Golang for internal tooling or automation
Experience with infrastructure monitoring and on-call practices using tools like Datadog and PagerDuty
Experience working with cross-discipline organizations that build data products
Experience in the gaming industry, particularly with online multiplayer games
Proficient in large-scale data manipulation across various data types
Demonstrated ability to troubleshoot and optimize complex ETL pipelines