Sr DataOps Engineer

Overview

Senior DataOps Engineer to operate, scale, and improve the data platforms that support Oportun's analytics, engineering, and business teams, focused on Databricks, AWS, data pipelines, databases, observability, automation, and production support.

What you'll do

• Administer and support Databricks workspaces, cluster policies, compute configurations, jobs, workflows, libraries, service principals, permissions, and platform integrations.
• Support Unity Catalog, including access governance, catalog and schema permissions, and secure data sharing.
• Monitor and troubleshoot Delta Live Tables, Spark jobs, Delta Lake workloads, and data pipelines, including failures, performance issues, recovery, and data-quality concerns.
• Maintain secure and reliable integrations between Databricks and AWS services, including S3, IAM, networking, VPC connectivity, and external data sources.
• Support AWS infrastructure used by the data platform, including EC2, VPC, IAM, security groups, networking, patching, and operational access.
• Support MariaDB/MySQL and MongoDB environments, including availability, monitoring, connectivity, backup coordination, performance troubleshooting, and recovery.
• Build and maintain monitoring, dashboards, logs, metrics, and alerts across Databricks, pipelines, databases, infrastructure, and integrations.
• Participate in on-call support and lead investigation, mitigation, recovery, communication, and root-cause analysis for production incidents.
• Build and maintain infrastructure and automation using Terraform, Terraform Enterprise, Git, GitHub Actions, CI/CD pipelines, and scripting.
• Automate repeatable operational activities such as provisioning, access configuration, monitoring deployment, recovery, and platform changes.
• Manage secure access controls, secrets, certificates, TLS configuration, service accounts, and IAM roles across platform services.
• Improve operational readiness through runbooks, recovery procedures, architecture diagrams, standards, escalation paths, and technical documentation.
• Partner with engineering and infrastructure teams to improve capacity planning, platform performance, cost visibility, and resource optimization.
• Look for practical ways to use AI and automation to improve troubleshooting, documentation, incident response, and operational efficiency.

What you'll need

• Strong experience supporting production data platforms, cloud infrastructure, or DataOps environments.
• Hands-on experience administering and supporting Databricks, including workspaces, jobs, workflows, compute, cluster policies, and access controls.
• Experience supporting Spark, Delta Lake, and Delta Live Tables workloads.
• Strong experience with AWS services such as EC2, VPC, IAM, S3, security groups, CloudWatch, and networking.
• Experience with infrastructure as code using Terraform and Terraform Enterprise or similar tools.
• Experience supporting MariaDB/MySQL and MongoDB in production environments.
• Strong understanding of monitoring, observability, alerting, and incident-management practices.
• Experience with CI/CD, Git, GitHub Actions, and automation using Bash, Python, PowerShell, or similar scripting languages.
• Experience troubleshooting platform performance, connectivity, permissions, certificates, TLS, and integration issues.
• Experience with production support, root-cause analysis, post-incident reviews, and on-call operations.
• Strong understanding of security and access concepts such as IAM, RBAC, secrets management, certificates, and secure connectivity.
• Strong communication and collaboration skills with the ability to work across Data Engineering, Analytics, Security, Infrastructure, Database, and application teams.

Nice to have

• Experience with Unity Catalog, Databricks SQL, Databricks CLI, REST APIs, and Databricks asset or deployment bundles.
• Experience with Kubernetes administration and production troubleshooting.
• Experience with monitoring tools such as Prometheus, Grafana, Datadog, or similar platforms.
• Experience with Rootly or similar incident-management platforms.
• Experience with MongoDB Atlas, Ops Manager, or comparable MongoDB tooling.
• Experience with MariaDB/MySQL replication, schema migrations, indexing, backup validation, and restore procedures.
• Experience with capacity planning, cloud cost optimization, and workload performance tuning.
• Experience implementing or improving data governance, compliance controls, or audit processes.
• Experience using AI-assisted tools to improve operations, troubleshooting, documentation, or automation.

Details

• Location: Remote - Mexico.
• Work mode: Remote.