Data Engineer

About the Position / Current Initiatives: The Data Operations Engineer will partner with infrastructure, platform, product, engineering, and data science teams to build and maintain scalable analytics and machine learning foundations. This role focuses on provisioning, enabling, scaling, and maintaining data platforms supporting both batch and real-time systems. The engineer will drive operational excellence through automation, observability, monitoring, continuous delivery practices, and self-healing capabilities while ensuring reliable, zero-downtime deployments. Job Must Haves: 5+ years Experience supporting and operating large-scale data, analytics, and ML infrastructure environments Strong experience with cloud platforms and hybrid cloud environments Hands-on experience with CI/CD pipelines Experience with Docker and Kubernetes Observability and monitoring experience using tools such as Splunk, Grafana, or Datadog Proficiency in Scala & one or more programming languages: Python, Go, Rust, or Java Experience with Infrastructure as Code (IaC), specifically Terraform Strong troubleshooting skills in distributed environments Experience handling production incidents, post-incident reviews, and operational excellence initiatives Ability to automate processes and develop self-service tools Strong communication skills and ability to work cross-functionally Job Nice to Haves: Spinnaker experience, Apache Spark, Trino or Pinot, Apache Iceberg, Atlas, Flink, Airflow or Luigi, Tableau, Snowflake, Databricks, MLFlow, Data Catalog tools, Jupyter Notebooks, Vector Databases, Cassandra, Experience with security controls, governance, and compliance validation, Infrastructure cost optimization experience