TELECOMMUTE Databricks Manager
Role details
Job location
Tech stack
Job description
-
Standardize data using industry frameworks to ensure IT-related data alignment (infrastructure-related information, infrastructure capacity, security-related, application runtime data, IT monitoring-related information, and additional meta-data)
-
Support and provide best practices on data mapping
-
Establish multi-zone / Medallion architecture to drive data and cost optimizations:
-
Bronze (raw telemetry)
-
Silver (cleaned/normalized)
-
Gold (aggregated/KPIs)
Design for 500TB+/day ingestion scale
Define standards for:
-
Delta Lake usage including Delta Tables / DLT
-
Table optimization (Z-ordering, partitioning)
-
Data lifecycle management
-
User workflows and use cases across various areas including line of business and IT
-
Knowledge of various Databricks capabilities including data engineering tools, Mosaic (AI/ML tools), Autoloader, Unity Catalog, Delta Tables / DLT, query builder, workspace - schema - table structures, Autoloader, LakeFlow, Genie, DataBricks Workflows / Jobs and additional Databricks components
-
Support FinOps (usage and capabilities cost controls) related activities including management and optimizations of compute, storage and DBU usage
-
Support Unity Catalog buildout including IAM and RBAC
-
Support and lead expertise
-
Support user-related best practices including use cases across various stakeholder roles, governance, user support, SLO / SLA development, predictive alerting and anomaly detection
-
Support pattern development and optimizations for data ingestion including streaming, batch and incremental
-
Knowledge and expertise in various data pipeline approaches and platforms to ensure data quality, data optimizations and reductions, ETL functions, data protection and high throughput and low latency
-
Support and provide expertise on semantic models
-
Support schema
Requirements
-
Experience working across different functional (application, infrastructure, security, compliance / audit, operations and business domains
-
Strong communication and organizational skills
-
Support delivery and management of the enterprise lakehouse architecture and implementation on large-scale cloud data platforms (Databricks)
-
Experience with Databricks usage in hyperscaler environments (Azure, Google Cloud Platform and Azure)
-
Support and lead implementation of best practices standards for SQL/PySpark development and usage