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# Databricks Admin Specialist - 6456969

- **Company:** Accenture
- **Location:** Culver City, CA, United States
- **Experience:** Experienced
- **Salary:** $105,498.0 - $126,298.0
- **Contract:** Permanent contract
- **Skills:** Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Processing, Snowflake, Reliability of Systems, Data Strategy, Data Pipelines, Databricks, Data Generation
- **Published:** August 28, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3367837306&tx=VT6863TTI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Minimum 4 years of work experience
 * Master proficiency in Databricks Administration is required.
 * High School Diploma/GED, * Expert proficiency in Snowflake Platform is recommended.
 * Expert proficiency in Data Migrations, Data Engineering, Data Pipelines, and Data Processing is suggested.

## Description

As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions that support data generation, collection, and processing. Your day-to-day activities will include creating data pipelines, ensuring data quality, and implementing extract, transform and load processes to migrate and deploy data across various systems. You are expected to be a subject matter expert, collaborate and manage the team to perform effectively, take responsibility for team decisions, engage with multiple teams, contribute to key decisions, and provide solutions to problems within your immediate team and across multiple teams., * Master proficiency in Databricks Administration is required. Expert proficiency in Snowflake (Platform) is recommended. Expert proficiency in Data Migrations, Data Engineering, Data Pipelines, and Data Processing is suggested.

 * Develop and optimize scalable data architectures to support evolving business needs and data strategies.
 * Lead efforts to troubleshoot complex data issues and implement robust solutions to enhance system reliability.
 * Collaborate with cross-functional teams to align data engineering efforts with organizational goals and project requirements.
 * Support and mentor colleagues by sharing expertise and promoting best practices in data engineering and administration.
 * Continuously evaluate emerging technologies and tools to improve data workflows and operational efficiency.


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