Enterprise Solutions Inc

Data Engineer

Princeton, NJ 08544

Posted: 09/06/2024 Job Number: z5G7h3l6a1kMvyS65NP3czbMc38oGLC3hbHRfmhzo9I= Pay Rate: 55-60 Hourly USD

Job Description


Role                      :            Data Engineer

Location                :           Princeton, NJ & Boston, MA (Fully onsite)

Role Type             :            Contract

 

Job Description:                                                                                                                                                                                                       
  • Minimum 10 + years with deep understanding of Databricks architecture and Apache Spark in Azure                                                                                                                                                                                                      
  • Design, develop, and optimize Spark-based data pipelines                                                                                                                                                                                                        
  • Collaborate with teams to align solutions with business needs                                                                                                                                                                                                
  • Strong proficiency in SQL, Python and Spark, with hands-on experience developing ETL processes and data pipelines                                                                                                                                                                                                   
  • Must have good work experience in ADLS, ADF & Data processing in Azure cloud and other RDBMS/appliances                                                                                                                                                                                                  
  • Knowledge of Data Modelling techniques (Data Vault 2.0), dimensional modelling and data warehousing concepts                                                                                                                                                                                                     
  • Understanding of RBAC.                                                                                                                                                                                               
  • Experience in Query Optimization techniques.       
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