Snowflake Data Engineer

Diverse Lynx LLC
Plano, TX, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$120,000.0 - $130,000.0
Working hours
Regular working hours

Tech stack

Amazon Web Services Microsoft Azure Cloud Computing Data as a Services Data Architecture Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Retrieval Data Systems Data Warehousing
+6 more
Document-Oriented Databases Performance Tuning Standard Sql Data Storage Technologies Snowflake Data Pipelines

Job description

Job Summary: We are seeking a skilled Data Engineer with a strong background in Snowflake to join our dynamic team. The ideal candidate will have 7 to 10 years of experience in data engineering, with a proven track record of designing, building, and maintaining data pipelines and architectures. You will play a crucial role in transforming raw data into actionable insights, ensuring data quality, and Eligible to workimizing data storage solutions., Design, develop, and maintain scalable data pipelines and ETL processes using Snowflake. Collaborate with data scientists and analysts to understand data requirements and deliver high-quality data solutions. Implement data models and architectures that support business intelligence and analytics initiatives. Monitor and Eligible to workimize data performance, ensuring efficient data retrieval and storage. Conduct data quality assessments and implement data governance practices. Work with cross functional teams to integrate data from various sources into Snowflake. Document data processes, architectures and workflows for future reference and compliance. Stay updated with the latest trends and technologies in data engineering and Snowflake.

Requirements

Mandatory Skills: Strong expertise in Snowflake, including data modeling, performance tuning, and security features. Proficient in SQL and experience with data warehousing concepts. Experience with ETL tools and data integration techniques. Solid understanding of data architecture and data governance principles. Familiarity with cloud platforms (AWS, Azure, or Eligible to workP) and their data services.

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