AWS Data Engineer with Snowflake (Only for H1B Transfer)

• Design, develop, and maintain ETL/ELT pipelines to ingest data from databases, APIs, files, and enterprise applications.
• Build and support AWS data solutions using Amazon S3, AWS Glue, AWS Lambda, Amazon CloudWatch, and IAM.
• Develop Snowflake tables, views, data models, and transformation workflows for reporting and analytics.
• Implement and manage data loading into Snowflake using stages, file formats, COPY INTO, and Snowpipe.
• Develop incremental data processing workflows using Snowflake Streams and Tasks.
• Write and optimize complex SQL queries and Python scripts for data processing and automation.
• Implement data quality checks, reconciliation, monitoring, error handling, and recovery mechanisms.
• Optimize Snowflake query performance, warehouse sizing, and compute costs.
• Apply security controls, including role-based access, encryption, and appropriate handling of sensitive data.
• Collaborate with business and analytics teams to translate requirements into technical solutions.
• Maintain documentation for data pipelines, mappings, models, and operational procedures.
• Participate in code reviews, testing, CI/CD, and production support.
  Required Skills and Qualifications
• Strong hands-on experience in data engineering with AWS and Snowflake.
• Strong SQL and Python programming skills.
• Experience with Amazon S3, AWS Glue, AWS Lambda, IAM, and CloudWatch.
• Practical knowledge of Snowflake architecture, virtual warehouses, stages, Snowpipe, Streams, and Tasks.
• Experience developing ETL/ELT pipelines, incremental loads, and change data capture (CDC).
• Understanding of data warehousing concepts, dimensional modeling, and star and snowflake schemas.
• Experience processing structured and semi-structured data, including JSON, CSV, and Parquet.
• Familiarity with workflow orchestration tools such as Apache Airflow, Amazon MWAA, or AWS Step Functions.
• Experience with Git, automated testing, and CI/CD practices.
• Strong troubleshooting, communication, and collaboration skills.
  Preferred Qualifications
• Experience with dbt for data transformation and testing.
• Experience with PySpark, Apache Spark, or Amazon EMR.
• Exposure to streaming technologies such as Amazon Kinesis or Apache Kafka.
• Experience with infrastructure as code using Terraform or AWS CloudFormation.
• Familiarity with data governance, metadata management, and data lineage.
• Relevant AWS or Snowflake certifications.

Please share the resume to