Data Platform Devops Engineer
Pubblicato il 03-10-2026 - Allianz in Italia
About the Job:
Join our data engineering and DevOps team to build, run, and continually improve modern data products on a cloud-first stack. You will collaborate in an agile, cross-functional environment to design and operate robust ELT pipelines and data models that power analytics and insights. In this role, you’ll combine hands-on development with DevOps practices—automating deployments, monitoring reliability, and ensuring quality—while supporting our migration and modernization initiatives on AWS and Snowflake.
What You Do:
• Collaborate with analysts and engineers in agile, cross-functional teams to deliver integrated data solutions.
• Build and operate data pipelines with AWS (S3, Glue, Lambda, Step Functions, CloudWatch), Snowflake, PySpark/Python, and dbt.
• Design and implement ELT pipelines, database structures, and data models aligned to business needs.
• Ensure reliability and performance via proactive monitoring, logging, and troubleshooting (CloudWatch, Dynatrace).
• Handle incident/problem management, root-cause analysis, and stakeholder communication.
• Execute releases and automate deployments using CI/CD and IaC (GitHub Actions, Terraform); follow DevOps best practices (GitHub, code reviews).
• Perform testing and quality checks to maintain code quality and data integrity.
• Drive continuous improvement and support adoption of new tools and technologies during platform migration.
What You Bring:
• Hands-on experience with Snowflake; AWS services (Glue, Lambda, S3, CloudWatch); and PySpark/Apache Spark.
• Proven track record designing and operating ELT/ETL pipelines, database design, and data modeling; familiarity with dbt or willingness to learn it.
• Data DevOps practices: GitHub-based version control and code reviews; CI/CD for data pipelines (e.g., GitHub Actions); IaC with Terraform; monitoring/logging (Dynatrace/CloudWatch).
• Strong problem-solving and communication skills; collaborative and able to work independently; service- and proc