Full Time

Data Engineer- (W2 only no relocation Dallas TX)

Mastech
Contract
Mid-Senior level
Artificial Intelligence
Dallas, TX
???* / year

Job Description

PLEASE DO NOT APPLY IF YOU ARE NOT LOCAL TO DALLAS, TX -ONLY W2


Greetings from Mastech Digital!

We currently have an open role with one of our clients that I believe may be of interest to you. This is a relationship-driven and urgent requirement, and the client is looking to interview and onboard a candidate as soon as possible. If this role is not a fit for you, I would greatly appreciate any referrals.


Please review the role details below and let me know your interest.

Please share your updated resume.


Job Title: AI & Data- Data Engineer

Location: – - Dallas TX-(Hybrid NO RELOCATION)

Job Type: Contract-(ONLY W2)


Job 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 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.
  • Advanced proficiency in Hadoop Administration is required.
  • Advanced proficiency in Data Processing is recommended.
  • Advanced proficiency in Data Migrations, Data Access, Data Engineering, and Data Pipelines is suggested. Develop and optimize scalable data architectures to support complex data workflows and analytics.
  • Collaborate with cross-functional teams to integrate diverse data sources and ensure seamless data flow.
  • Support and mentor colleagues by sharing expertise and promoting best practices in data engineering.
  • Analyze and troubleshoot data-related issues to enhance system reliability and performance. Contribute to the continuous improvement of data management processes and tools


Thanks and regards,

Prachi.


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