Data Engineer w Databricks

SolutionIT

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profile Job Location:

New York City, NY - USA

profile Monthly Salary: Not Disclosed
Posted on: 19 hours ago
Vacancies: 1 Vacancy

Job Summary

Solution IT Inc. is looking for Data Engineer w/ Databricks for one of its clients at NYC NY/ HYBRID

Job Title: Data Engineer w/ Databricks

Responsibilities:

  • Develop optimize and maintain Databricks notebooks for ETL and data transformation.
  • Design and implement scalable data pipelines using Databricks and Azure Data Factory.
  • Apply strong knowledge of distributed computing concepts to large-scale data processing.
  • Work with data lake architectures and Delta Lake for reliable and performant data storage.
  • Automate data quality checks monitoring and logging.
  • Integrate data from multiple cloud sources such as Azure Blob Data Lake Storage and SQL/NoSQL databases.
  • Perform data modeling and schema design for analytical workloads.
  • Implement CI/CD pipelines for Databricks notebooks and jobs.
  • Manage workspace administration cluster management and job orchestration in Databricks.

Required Skills

  • Proven experience with Databricks for large-scale data processing and analytics..
  • Familiarity with cloud data platforms preferably Azure.
  • Understanding of data engineering best practices and distributed systems.
  • Experience with data pipeline orchestration and automation

Work Site: NYC NY/ (Hybrid)

Duration: 6 Months

Expected Start Date: Immediate

Number of Positions: 1

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About Solution IT

Solution IT is a national IT consulting company specializing in: Technology Staffing and Oracle E-Business Solutions based in Boston Massachusetts.
Solution IT Inc. is looking for Data Engineer w/ Databricks for one of its clients at NYC NY/ HYBRID Job Title: Data Engineer w/ Databricks Responsibilities: Develop optimize and maintain Databricks notebooks for ETL and data transformation. Design and implement scalable data pipelines using Databr...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala