(W2 ONLY) Sr. AWS Data Engineer

Job Title: AWS Senior Data Engineer
 

DESCRIPTION:
WANTS

• Primary Skills : AWS EMR , GLUE, AIRFLOW, ICEBERG, REDSHIFT, RDS , IDMC, AMAZON KIRO and CI/CD
• Candidate should Design and Develop Data Pipelines and Support them.
• Candidate will work from Torrance CA location, 4 days onsite and 1 day Work from Home, Should be able to come work all five days if required.
• Project Number: PR11965

Experience:

• 5+ years of experience in data engineering, database design, ETL processes, and data warehousing.
• 3+ years of experience with AWS tools and technologies (S3, EMR, Glue, Athena, RedShift, RDS, Spectrum and Airflow) 2+ years of experience with CI/CD tools.
• Strong knowledge of data storage and processing technologies, including databases  and data lakes based distributed computing frameworks (e.g., Hadoop, Spark).
• 3+ in programming languages such as Python, Java, or Scala.
  • Nice to have Informatica Cloud tool experience (IDMC)
  • Nice to have Agentic AI experience with Amazon Kiro

Detailed Responsibilities:

Develop and Maintain Data Integration Solutions:

• Design and implement data integration workflows using AWS Glue/EMR,AWS MWAA(Airflow), Lambda, Redshift
• Demonstrate proficiency in Pyspark, Apache Spark and Python for data processing large datasets
• Ensure data is accurately and efficiently extracted, transformed, and loaded into target systems.

Ensure Data Quality and Integrity:

• Validate and cleanse data to maintain high data quality.
• Ensure data quality and integrity by implementing monitoring, validation, and error handling mechanisms within data pipelines

Optimize Data Integration Processes:

• Enhance the performance, optimization of data workflows to meet SLAs, scalability of data integration processes and cost-efficiency on AWS     cloudinfrastructure.
• Identify and resolve performance bottlenecks, fine-tuning queries, and optimizing data processing to enhance Redshift's performance
• Regularly review and refine integration processes to improve efficiency.

Support Business Intelligence and Analytics:

• Translate business requirements to technical specifications and coded data pipelines
• Ensure timely availability of integrated data for business intelligence and analytics.
• Collaborate with data analysts and business stakeholders to meet their data requirements.

Maintain Documentation and Compliance:

• Document all data integration processes, workflows, and technical & system specifications.
• Ensure compliance with data governance policies, industry standards, and regulatory requirements.