Senior Data DevOps Engineer

Appliscale is an independent Technology Consultancy specializing in bespoke, cloud-based systems and full-cycle engineering across industries including gaming, proptech, legaltech, and adtech. They partner with startups, scaleups, and Fortune 500 companies worldwide and focus on building intelligent agents for automation and scalable ecosystems.

• Minimum of 5 years commercial work experience in software engineering, data engineering, or related fields
• Bachelor's or higher degree in Computer Science, Software Engineering, or related fields
• Coding skills with commercial experience in Java, Python, or Golang
• Experience with Infrastructure as Code tooling such as Terraform
• Experience with CI/CD tooling, e.g., GitHub Actions, Jenkins, Docker
• Experience with streaming and schema-driven systems like 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 with DatabricksDelta Live Tables and Unity Catalog
• Experience with AWS services such as Kafka/MSK, S3, IAM, and VPC/networking
• Experience with Buf, Protobuf tooling, or JSON-to-Protobuf migration
• Familiarity with Golang for internal tooling or automation
• Experience with infrastructure monitoring and on-call using Datadog and PagerDuty
• Ability to troubleshoot and optimize complex ETL pipelines

• Design, build, and operate services and pipelines for analytics data ingestion, schema management, and delivery into Databricks
• Modernize legacy platform components by migrating to modern Java and application standards
• Build automation, CI/CD flows, and integration test coverage for safe platform changes
• Design and maintain production infrastructure in AWS using Infrastructure as Code tooling such as Terraform
• Improve data quality via schema validation, metadata capture, lineage tracking, and guardrails
• Build tooling and paths to help internal customers migrate to new ingestion and schema standards
• Collaborate with teams on design docs, rollout plans, and implementation strategies
• Monitor systems, investigate incidents, and provide 3rd line on-call support for analytics services
• Support performance, reliability, and cost optimization across ingestion and processing flows