AWS Data Engineer

We are seeking a highly skilled and experienced Data Engineer with 9 years of experience to design, develop, and maintain scalable data pipelines and infrastructure on AWS. The ideal candidate will have strong expertise in AWS Glue, Redshift, Athena, and related AWS services. The role demands end-to-end ownership of data workflows, performance optimization, and delivering reliable data solutions to support business intelligence, analytics, and machine learning initiatives. 

Design, build, and manage scalable and high-performance ETL/ELT pipelines using AWS Glue, PySpark, and Step Functions. 
Develop and optimize data warehousing solutions using Amazon Redshift for structured and semi-structured data. 
Implement efficient query solutions using Amazon Athena, Redshift Spectrum, and data lake patterns. 
Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver reliable solutions. 
Ensure data quality, integrity, and compliance through robust validation and transformation techniques. 
Implement monitoring, logging, and alerting solutions for data pipeline health using CloudWatch and other AWS-native tools. 
Manage and orchestrate jobs via AWS Glue Workflows, Step Functions, or custom schedulers (e.g., Apache Airflow). 
Tune performance for ETL jobs and SQL queries in Redshift and Athena for faster execution. 
Handle data modeling, schema design, and partitioning strategies for large-scale datasets. 
Stay updated with AWS data services and recommend architecture improvements and cost optimizations. 


Skill
AWS Glue (ETL/PySpark) 
Amazon Redshift
Amazon Athena
Data Lake (S3-based)
SQL (T-SQL, Redshift SQL)
ETL Design Data Pipelines
Data Modeling (Star, Snowflake)
AWS Lambda & Step Functions
AWS IAM, CloudWatch, SNS/SQS