Location: Remote
Employment Type: Full-Time
Overview
Rialtes is seeking a Databricks Support Analyst to manage platform operations, ensure reliability of clusters and jobs, and support development of data workflows. Role requires hands-on experience with Databricks administration, SQL-based development, and basic Python.
Key Responsibilities
Primary: Platform Support
- Monitor and maintain Databricks clusters, jobs, workflows, and schedules.
- Troubleshoot issues related to compute resources, job failures, data ingestion completeness, schema changes, and data accuracy.
- Manage user provisioning, access controls, workspace permissions, and catalogs using Unity Catalog aligned with governance standards.
- Ensure cost-optimized cluster usage and enforce security, tagging, and compliance policies.
- Collaborate with Cloud Ops, Data Engineering, and InfoSec teams to resolve platform-wide incidents.
Secondary: Design & Development
- Assist in building Databricks workflows for ETL, analytics, and machine learning pipelines.
- Support development and optimization of notebooks and scriptsprimarily SQL, with some Python for transformations and validations.
- Implement best practices for job cluster configuration, Photon acceleration, Delta Lake, and Unity Catalog integration.
- Participate in unit testing, functional testing, UAT cycles, and production migration of Databricks jobs.
- Contribute to documentation including runbooks, SOPs, job catalogs, and data lineage.
Qualifications
- 5 years of experience in Databricks, data engineering support, or cloud platform operations.
- Strong SQL skills; working knowledge of Python preferred.
- Hands-on experience with Databricks clusters, job orchestration, Delta Lake, and Unity Catalog.
- Understanding of ETL workflows, CI/CD for data pipelines, and cloud environments (AWS/Azure/GCP).
- Strong debugging skills for job failures, performance bottlenecks, and ingestion issues.
- Ability to work in fast-paced environments with cross-functional teams.
Nice-to-Have
- Databricks Certified Associate or equivalent.
- Exposure to MLflow, Data Quality (DQ) frameworks, or Databricks Workflows orchestration.
- Experience with Git, DevOps tools, or monitoring solutions (CloudWatch, Azure Monitor, etc.).