Sr DataOps Engineer

Accountabilities

• Administer and support Databricks workspaces, compute configurations, cluster policies, jobs, workflows, libraries, service principals, permissions, and platform integrations.

• Support Unity Catalog and implement secure data access governance, catalog and schema permissions, and data-sharing controls.

• Monitor and troubleshoot Spark jobs, Delta Lake workloads, Delta Live Tables, and data pipelines, addressing failures, performance bottlenecks, recovery needs, and data-quality issues.

• Maintain secure, reliable integrations between Databricks and AWS services, including Amazon S3, IAM, VPC connectivity, networking, and external data sources.

• Support AWS infrastructure for data platforms, including EC2, VPC, IAM, security groups, patching, networking, and operational access.

• Maintain production database environments across MariaDB/MySQL and MongoDB, including availability, monitoring, connectivity, backups, performance troubleshooting, and recovery.

• Build and maintain observability solutions, including dashboards, logs, metrics, and alerts across data platforms, pipelines, databases, infrastructure, and integrations.

• Participate in on-call rotations and lead production incident investigation, mitigation, recovery, stakeholder communication, and root-cause analysis.

• Develop and maintain infrastructure-as-code and automation solutions using Terraform, Terraform Enterprise or equivalent tools, Git, GitHub Actions, CI/CD pipelines, and scripting languages.

• Automate recurring operational tasks such as infrastructure provisioning, access configuration, monitoring deployment, recovery procedures, and platform changes.

• Manage security controls, secrets, certificates, TLS configurations, service accounts, and IAM roles across platform services.

• Improve operational readiness through runbooks, recovery procedures, architecture diagrams, technical standards, escalation paths, and documentation.

• Collaborate with Data Engineering, Analytics, Security, Cloud Infrastructure, Database, and application teams to improve capacity planning, platform performance, cost visibility, and resource utilization.

• Identify practical applications for AI-assisted tools and automation to enhance troubleshooting, incident response, documentation, and operational efficiency.

Requirements

• Strong experience supporting production data platforms, cloud infrastructure, or DataOps environments.

• Hands-on experience administering Databricks, including workspaces, jobs, workflows, compute resources, cluster policies, and access controls.

• Experience supporting Apache Spark, Delta Lake, and Delta Live Tables workloads.

• Strong knowledge of AWS services, including EC2, VPC, IAM, S3, security groups, CloudWatch, and cloud networking.

• Experience with infrastructure as code using Terraform, Terraform Enterprise, or comparable tools.

• Production experience supporting MariaDB/MySQL and MongoDB environments.

• Strong understanding of monitoring, observability, alerting, incident management, and production support practices.

• Experience with CI/CD, Git, GitHub Actions, and automation using Bash, Python, PowerShell, or similar scripting languages.

• Proven troubleshooting skills across platform performance, connectivity, permissions, certificates, TLS, and service integrations.

• Experience with root-cause analysis, post-incident reviews, recovery procedures, and on-call operations.

• Strong understanding of security and access management, including IAM, role-based access control (RBAC), secrets management, certificates, and secure connectivity.

• Excellent communication and collaboration skills, with the ability to coordinate effectively across engineering, analytics, security, infrastructure, database, and application teams.

• A proactive, hands-on mindset focused on identifying root causes, resolving complex technical challenges, improving reliability, and reducing operational overhead.

• Curiosity about AI and a willingness to experiment with AI-assisted tools, learn new capabilities, and apply sound technical judgment to practical use cases.

Nice to have:

• Experience with Unity Catalog, Databricks SQL, Databricks CLI, REST APIs, and Databricks asset or deployment bundles.

• Kubernetes administration and production troubleshooting experience.

• Familiarity with observability platforms such as Prometheus, Grafana, Datadog, or similar tools.

• Experience with Rootly or comparable incident-management platforms.

• Familiarity with MongoDB Atlas, Ops Manager, or equivalent MongoDB administration tools.

• Experience with MariaDB/MySQL replication, schema migrations, indexing, backup validation, and restore procedures.

• Knowledge of capacity planning, cloud cost optimization, and workload performance tuning.

• Experience implementing or improving data governance, compliance controls, and audit processes.

• Experience using AI-assisted tools to improve operational workflows, troubleshooting, documentation, or automation.

Benefits

Eligible employees in Mexico may receive a competitive compensation and benefits package designed to support their physical, financial, and professional well-being. Benefits include:

• Medical insurance.

• Savings fund.

• Life insurance.

• Internet and electricity allowance.

• Paid time off, including vacation and parental leave.

• A remote-work opportunity, as indicated in the original job listing.

• Opportunities to explore AI tools and apply automation to improve operational efficiency and technical workflows.