Working knowledge of DataOps practices and tooling - including Git-based workflows, CI/CD (e.g., GitHub Actions, GitLab CI, AWS CodePipeline), Infrastructure-as-Code (Terraform or CloudFormation), automated data testing, and pipeline observability - is highly preferred. Working knowledge of modern data platform technologies - such as cloud data warehouses/lakehouses (Snowflake, Databricks, BigQuery), streaming (Kafka, Kinesis), and data catalog/governance tools - used to enable a data mesh is highly preferred.