Senior Databricks Data Engineer for AI/ML Pipelines & Azure

TechRuiter

Las Vegas (NV)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

TechRuiter in Las Vegas, NV is seeking a senior Data Engineer to design scalable data pipelines and support AI/ML initiatives. This onsite role requires 4 days per week in the office and full-time employment. U.S. Citizens and Green Card holders only.

You will build ingestion and transformation workflows, develop APIs and data products, ensure data quality, and collaborate with teams to deliver robust data solutions leveraging Databricks and Azure services.

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • 10+ years of experience in Data Engineering.
  • Strong expertise in Databricks, Apache Spark, and cloud-based data platforms.
  • Proficiency in Python and SQL.
  • Hands-on experience with Azure dataservices and REST API development.
  • Experience with DevOps, CI/CD pipelines, and Agile methodologies.

Responsibilities

  • Design and develop scalable batch and real-time datapipelines.
  • Build robust data ingestion, transformation, and analytics workflows.
  • Develop intelligent APIs and data products to support AI and business applications.
  • Ensure high data quality, reliability, and performance.
  • Collaborate with cross-functional teams to deliver scalable data solutions.
  • Support Azure-based data platforms for BI and AI/ML initiatives.
  • Participate in code reviews and implement CI/CD best practices.

Skills

Databricks
AI/ML
Python
DevOps & CI/CD
SQL

Education

Bachelor's degree in Computer Science, Engineering, or a related technical field

Job description

TechRuiter in Las Vegas, NV is seeking a senior Data Engineer to design scalable data pipelines and support AI/ML initiatives. This onsite role requires 4 days per week in the office and full-time employment. U.S. Citizens and Green Card holders only.

You will build ingestion and transformation workflows, develop APIs and data products, ensure data quality, and collaborate with teams to deliver robust data solutions leveraging Databricks and Azure services.

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