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Azure Databricks Engineer
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Capgemini Seattle, United StatesSogeti is a leading provider of professional technology services, specializing in Application Management, Infrastructure Management and High-Tech Engineering. Sogeti offers cutting-edge solutions around Testing, Business Intelligence, Mobility, Cloud and Security, combining world ...
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Sr. Engineering Manager
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Data Engineer
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Senior Software Engineer
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Senior Software Engineer
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Solution Developer 3,
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Senior Data Modeler
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Data Product Manager
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Data Engineer II
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Machine Learning Data Engineer Specialist
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lead gcp data engineer
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Senior Machine Learning Engineer
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Sr Engineer
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Machine Learning Data Engineer Specialist
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Prodigy Resources Seattle, United StatesAbout the role: · We are looking for a Senior Machine Learning Engineer to help us build a brand-new financial technology platform for the future. We look for people who operate like owners, who loves to learn, have grit, and operate with integrity and empathy. You're encouraged ...
Databricks Engineer - Seattle, United States - Intellectt Inc
![Intellectt Inc background](https://contents.bebee.com/companies/us/intellectt-inc/background-u6709.png)
Description
Architect Unity Catalog: Provide centralized access control, auditing, lineage, and data discovery capabilities across Databricks workspaces.
Organize Data Assets: Define and categorize structured and unstructured data within the Unity Catalog.
Design Azure Cloud-Based Architecture: Implement Data Warehousing and Governance architecture with Lakehouse paradigm.
Define Access Policies: Ensure secure and consistent access management at a granular level (rows, columns, features) across platforms.
Leverage Delta Sharing: Enable easy data sharing across regions and platforms.
Ensure Secure Data Sharing: Share data and AI assets with minimal replication for a unified user experience.
Integrate Technical Functionality: Ensure data accessibility, accuracy, and security.
Empower Data Analysts and ETL Engineers: Discover and classify data, notebooks, dashboards, and files across clouds and platforms.
Implement Single Permission Model: Establish a unified permission model for data and AI assets.
Monitoring and Observability: Utilize AI for automated monitoring, error diagnosis, and data quality maintenance.
Set Up Alerts: Configure alerts for Personally Identifiable Information (PII) detection and operational insights.
Collaborate with Data Scientists and Engineers: Foster adoption of the Unity Catalog among stakeholders.
Provide Training and Documentation: Ensure effective usage and compliance with governance policies.
Skills:
Development and Configuration: Expertise in developing and configuring Unity Catalog.
Data Governance Principles: In-depth understanding of data governance principles, especially pertaining to data cataloging, access control, lineage, and metadata management.
Data Warehouse Solutions: Designed data warehouse and data lake solutions, including data processing pipelines using PySpark in Databricks.
Data Modelling: Experience in Data Modelling on Databricks [Delta Table] for transactional and analytical purposes.
Data Lake Management: Developed pipelines for loading data into the Data Lake.
Databricks Proficiency: Proficient in Databricks Platform components such as Databricks SQL, Delta Live Tables, Databricks Repos, and Task Orchestration.
SQL Skills: Strong SQL skills for data querying and management.
Data Model Optimization: Ability to design and optimize data models for structured and unstructured data.
Compute Resource Management: Understanding of managing compute resources, clusters, and workspaces.