SEMANTIC & GENIE ENGINEER (DATABRICKS)
- Hiring from
- India
- Work type
- Remote
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Job Description
Summary
We are seeking a highly skilled Semantic & Genie Engineer to join our IT Services team, focusing on advanced data architecture and intelligent automation within the Databricks ecosystem. This pivotal role is designed to leverage cutting-edge technologies to enhance data governance, optimize query performance, and develop sophisticated multi-agent orchestration solutions. The ideal candidate will bridge the gap between complex data engineering and generative AI capabilities, ensuring robust data quality and seamless integration of semantic layers across our platforms.
Responsibilities
- Design and implement Unity Catalog strategies to manage data access, lineage, and governance effectively.
- Architect and maintain Delta Lake structures to ensure high-performance data storage and processing.
- Conduct comprehensive data profiling and establish rigorous validation frameworks to uphold data integrity.
- Optimize complex SQL queries and database performance to support real-time analytics and reporting needs.
- Develop and deploy custom applications using Python, Streamlit, and Databricks Apps to visualize insights and automate workflows.
- Engineer advanced multi-agent systems and Databricks Genie Agents to drive autonomous data operations and decision-making.
- Configure and monitor Databricks Metric Views to track key performance indicators and system health.
- Manage version control and collaborative development processes using Git for all codebases and configurations.
- Integrate Machine Learning Pipelines (MCP) to enhance the predictive capabilities of data solutions.
Requirements
Requirements:
- Minimum of 5 years of professional experience in data engineering or related technical fields.
- Proficiency in Python programming and advanced SQL for data manipulation and analysis.
- Deep expertise with Databricks ecosystem components, including Unity Catalog, Delta Lake, and Databricks Genie.
- Strong background in data quality assurance, profiling techniques, and validation methodologies.
- Demonstrated ability to perform query optimization and tune data pipelines for maximum efficiency.
- Experience building interactive dashboards and applications using Streamlit and Databricks Apps.
- Knowledge of multi-agent orchestration patterns and the implementation of Genie Agents/Spaces.
- Familiarity with Git version control systems and collaborative development practices.
- Understanding of Machine Learning Pipelines (MCP) and their integration into data workflows.
