Williams-Sonoma
Website:
williams-sonomainc.com
Job details:
Job Details - DataOps / DevOps Engineer
Azure | CI/CD | Data Platform | Observability
DataOps | DevOps | Airflow/ADF | Spark/Kafka | Snowflake | Python/SQL | MLOps
Role Overview
We are looking for a highly motivated DataOps / DevOps Engineer to build and scale reliable, automated, and efficient deployment pipelines across our modern data platform. This role focuses on enabling seamless collaboration between Data Engineering, Analytics, and AI/ML teams by implementing strong DevOps and DataOps practices ensuring platform reliability, observability, governance, and operational excellence.
You will be responsible for implementing CI/CD workflows, deployment automation, monitoring, infrastructure reliability, and operational support for batch and real-time data ecosystems in a cloud-based Azure environment. This role plays a critical part in supporting analytics, AI/ML, and enterprise-scale data initiatives across the organization.
Key Responsibilities
▪ Implement and manage CI/CD pipelines for data workflows, including automated testing, deployment, rollback, and version control.
▪ Build and scale reliable, automated, and efficient deployment pipelines for data and AI/ML platforms.
▪ Support deployment and operationalization of batch and real-time data systems in collaboration with Data Engineering teams.
▪ Manage and optimize orchestration and workflow tools such as Airflow, Azure Data Factory, or equivalent platforms.
▪ Ensure platform reliability through robust monitoring, logging, alerting, and observability frameworks.
▪ Define and manage SLAs/SLOs, ensuring uptime, stability, and operational performance of data platforms.
▪ Optimize cloud infrastructure and workloads for performance, scalability, and cost efficiency.
▪ Support distributed systems and large-scale processing platforms using technologies such as Spark, Kafka, and Snowflake.
▪ Collaborate with Data Engineers, ML Engineers, Data Scientists, and Analysts to enable production-ready data and AI solutions.
▪ Support deployment and operational management of AI/ML Ops pipelines and model lifecycle workflows.
Required Skills & Experience
▪ 2–3 years of experience in DataOps, DevOps, Platform Engineering, or Cloud Engineering roles.
▪ Strong understanding of CI/CD concepts, deployment automation, and DevOps best practices.
▪ Hands-on experience with Azure cloud platform (Azure DevOps, Data Factory, Databricks, Data Lake, etc.) or equivalent cloud ecosystems.
▪ Experience with CI/CD tools such as Azure DevOps, Jenkins, or GitHub Actions.
▪ Familiarity with big data and distributed systems such as Spark, Kafka, and Snowflake.
▪ Strong proficiency in SQL, Python/Shell scripting, and Linux system operations.
▪ Experience with monitoring and observability tools such as Prometheus, Grafana, or equivalent.
▪ Strong troubleshooting, debugging, and operational support skills.
Good to Have
▪ Experience with Airflow/Dagster and workflow orchestration platforms.
▪ Exposure to AI/ML Ops pipelines, model deployment workflows, and feature engineering support.
▪ Knowledge of Infrastructure as Code (IaC) using Terraform, ARM templates, or Azure Bicep.
▪ Understanding of Delta Lake / Lakehouse architecture.
▪ Familiarity with data quality, governance, lineage, and cataloging frameworks.
▪ Exposure to Kubernetes, containerization, and cloud-native deployment practices.
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