Role Data Engineering
Overview
Genesis Computing offers AI data agents designed to automate data workflows, allowing users to focus on high-impact tasks. These agents come with advanced skills and tools to securely automate data workflows.
Key Features:
- Built-in integrations and tools
- Autonomous orchestration of tasks
- Adaptable workflows that improve over time
Use Cases:
- Data Engineering: Building and optimizing data pipelines
- Data Ops: Fixing data pipeline problems
- Business Analysis: Performing advanced analytics
Benefits:
- Automated routine tasks
- Improved data team efficiency
- Faster product development cycles
Capabilities
- Automates data workflows
- Builds and optimizes data pipelines
- Fixes data pipeline problems
- Performs advanced analytics
- Integrates with Slack, Teams, Email, Google Sheets, Jira, and Git
- Deconstructs and delegates complex tasks to specialized data agents
- Operates natively on the Snowflake AI Data Cloud
- Automates routine tasks for data pipeline creation and maintenance
- Manages data platforms
- Resolves DBT and Dagster pipeline failures
- Automates data collection and analysis
- Deploys via pip install
- Leverages built-in security features of data platforms
- Understands data landscape, permissions, and metadata
- Adapts and improves workflows by learning from interactions
- Allows customization and goal setting
- Provides clear explanations of AI actions
- Automates data logic migration
- Finds semantically relevant data sets
- Runs SQL queries
- Executes Python dataframe code
- Automates and executes multi-step workflows
- Builds and optimizes data models in Snowflake
- Executes, stores, and updates structured scripts (Python/SQL)
- Enriches workflows with automated web data retrieval