Data Bricks

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profile Job Location:

Boston, NH - USA

profile Monthly Salary: Not Disclosed
Posted on: 9 hours ago
Vacancies: 1 Vacancy

Job Summary

Data Bricks
Boston/Jersey City
8-12 Years
Local Profiles only
Job Description:
Design develop and maintain scalable data pipelines and ETL processes using Python Databricks and AWS Glue.
Build and optimize data warehouses and data lakes on PySpark and AWS platforms.
Implement data ingestion transformation and orchestration workflows using AWS Step Functions Lambda and Glue Jobs.
Monitor troubleshoot and optimize pipeline performance using AWS CloudWatch and other monitoring tools.
Collaborate with data analysts data scientists and business stakeholders to define data requirements and deliver reliable datasets.
Ensure data quality governance and security across all data systems and workflows.
Automate repetitive data engineering tasks and contribute to building reusable frameworks and templates.
Support continuous improvement by adopting best practices for CI/CD version control and infrastructure-as-code (IaC).

Donato Technologies Inc. is a trusted IT staffing consulting and software development partner headquartered in Dallas Texas. We support clients across industries by understanding their unique business needs and delivering tailored technology and workforce solutions. Our focus is on connecting the right talent with the right opportunity-ensuring clients receive dependable skilled professionals and candidates receive meaningful career growth and support. We work closely with small to mid-sized organizations to provide flexible high-quality services that drive performance innovation and long-term success.

Data Bricks Boston/Jersey City 8-12 Years Local Profiles only Job Description: Design develop and maintain scalable data pipelines and ETL processes using Python Databricks and AWS Glue. Build and optimize data warehouses and data lakes on PySpark and AWS platforms. Implement data ingestion trans...
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Key Skills

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