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Data Engineer with GMI XMX Engineering Ops - W2 Position (Locals only)
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ASCII Group LLC
San Jose, CA (In Person)
$124,800 Salary, Full-Time
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Job Description
W2 Position only The following requirement is open with our client.
Client :
TCS Title :
Data Engineer withGMI XMX Engineering Ops Location :
San Jose CA (Onsite)Duration :
12Months Rate :
$60/hr on W2Relevant Experience :
LOCAL CANDIDATES ONLY
Detailed Job Description:
We are looking for an experienced Data Engineer with strong expertise in Azure Data Services, Databricks, SQL, and modern data engineering practices. The ideal candidate must possess a 4-year Bachelor''s degree in Computer Science Engineering and have at least 3 years of experience performing Data Architect responsibilities. This role involves designing scalable data architectures, building robust data pipelines, and supporting enterprise analytics platforms handling large-scale structured and unstructured datasets.Job Responsibilities:
- Design and implement scalable enterprise data architectures and data models.
- Build, optimize, and maintain ETL/ELT pipelines for data ingestion and transformation.
- Develop and manage data workflows using Airflow/Astronomer.
- Work extensively with Azure Data Services and Databricks for data processing and analytics.
- Design and manage large-scale structured and unstructured data platforms.
- Collaborate with business and engineering teams to translate requirements into scalable data solutions.
- Ensure data quality, governance, security, and performance across data platforms.
- Optimize SQL queries, database performance, and data processing workflows.
- Support cloud-based data modernization and architecture initiatives.
- Provide technical leadership and best practices for data engineering and architecture.
Must Have Skills:
- Bachelor''s Degree in Computer Science Engineering (4-year degree mandatory).
- Minimum 8+ years of experience in Data Engineering/Data Management.
- Minimum 3+ years of experience in a Data Architect role.
- Strong SQL and database fundamentals.
- Hands-on experience with Azure Data Services.
- Working knowledge of Databricks.
- Experience designing and implementing ETL/ELT workflows.
- Experience building and managing data pipelines.
- Hands-on experience with Airflow or Astronomer workflow orchestration.
- Experience handling large-scale structured and unstructured datasets.
- Strong understanding of data architecture, data modeling, and data integration.
- Experience with cloud-based data platforms and analytics solutions.