• US Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• W2-Permanent

• W2-Contract

• Contract to Hire

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 10th May 2023

Must Have Skills:
-AWS
-Azure
-Cloud Computing

Nice to have skills:
-AWS
-Cloud Computing

Detailed Job Description:
-An experienced ETL Architect to design and implement data integration solutions that can handle large volumes of data both on AWS and On-Premise environments. The successful candidate will work with our data engineering team to develop ETL pipelines that can transform, validate and load data from various sources including real-time streams into data lakes and data platforms. The candidate should have a strong background in Spark and Java and be able to provide technical leadership in designing and implementing ETL solutions.
• 10+ years of experience in designing and implementing ETL solutions using Spark and Java for batch, micro-batch and real-time/near real-time data sources.
• Strong experience with AWS data integration services such as Glue, Kinesis and EMR.
• Strong experience with Kafka
• Experience with data warehousing and data lake concepts and architectures both On Premise and using AWS Services
• Strong knowledge of SQL and data modeling concepts.
• Strong problem-solving skills and ability to work independently.
• Excellent communication and collaboration skills.
• AWS or other relevant certifications are a plus.

Minimum years of experience: 8-10 years
Certifications Needed :No

Top 3 responsibilities you would expect the Subcon to shoulder and execute:
-Design and develop data integration solutions using Spark and Java that can handle large volumes of data.
-Provide Architectural guidance to provide performant and cost effective options for data ingestion and transformation frameworks and solutions.
-Work with data engineering team to identify data sources and develop frameworks and pipelines that can integrate data into data lakes, data warehouses and other data platforms.