Job Description
7+ years of Data Engineering
experience with strong AWS cloud expertise and architecture understanding. Hands-on experience with
AWS S3, Glue, Lambda, Athena, and Step Functions . Experience building APIs using
API Gateway with Lambda/ECS/EKS . Strong experience in
S3 bucket design, partitioning, lifecycle policies, IAM, and encryption . Hands-on
Amazon Athena
experience for data validation, ad-hoc queries, and performance optimization on large S3 datasets. Strong
ETL/ELT pipeline development and optimization
experience with AWS Glue and Step Functions. Experience with
file-based ingestion , including SFTP, file drops, inbox/outbox, and event-driven S3 ingestion. Experience migrating data from
RDBMS/data warehouses to AWS S3 or Redshift . Strong
Python and SQL
skills for data processing and automation. Experience designing
data lake architectures
using Raw, Curated, and Consumption layers. Strong understanding of
partitioning, distributed processing, data quality, and pipeline optimization . Experience with event-driven pipelines using one or more of
SQS, SNS, EventBridge, Kafka, or Kinesis . Strong
debugging, monitoring, troubleshooting, and performance optimization
skills.
experience with strong AWS cloud expertise and architecture understanding. Hands-on experience with
AWS S3, Glue, Lambda, Athena, and Step Functions . Experience building APIs using
API Gateway with Lambda/ECS/EKS . Strong experience in
S3 bucket design, partitioning, lifecycle policies, IAM, and encryption . Hands-on
Amazon Athena
experience for data validation, ad-hoc queries, and performance optimization on large S3 datasets. Strong
ETL/ELT pipeline development and optimization
experience with AWS Glue and Step Functions. Experience with
file-based ingestion , including SFTP, file drops, inbox/outbox, and event-driven S3 ingestion. Experience migrating data from
RDBMS/data warehouses to AWS S3 or Redshift . Strong
Python and SQL
skills for data processing and automation. Experience designing
data lake architectures
using Raw, Curated, and Consumption layers. Strong understanding of
partitioning, distributed processing, data quality, and pipeline optimization . Experience with event-driven pipelines using one or more of
SQS, SNS, EventBridge, Kafka, or Kinesis . Strong
debugging, monitoring, troubleshooting, and performance optimization
skills.
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