Job Summary

The Senior AWS Data Engineer is responsible for designing, developing, and maintaining scalable cloud-based data engineering solutions that support enterprise analytics and business intelligence initiatives. This role involves building high-performance data pipelines, developing ETL processes, implementing data warehousing solutions, and leveraging AWS cloud technologies to deliver secure, reliable, and scalable data platforms. The ideal candidate will have strong expertise in AWS, Snowflake, ETL development, data warehousing, and cloud-native data processing technologies.

Key Responsibilities
• Collaborate with product and business teams to gather requirements and propose scalable data engineering solutions.
• Analyze business and technical requirements to design effective data pipeline architectures.
• Design, develop, and maintain scalable ETL and ELT pipelines for enterprise data platforms.
• Build and optimize cloud-native data workflows using AWS services and modern data engineering tools.
• Design and implement data warehouse solutions to support business intelligence and analytics.
• Develop high-volume data processing pipelines in cloud environments.
• Build and maintain data pipelines using Informatica Intelligent Cloud Services (IICS), Alteryx, or similar ETL tools.
• Develop and optimize data processing solutions using Snowflake.
• Implement streaming data pipelines using Apache Kafka.
• Perform data cleansing, transformation, validation, and data quality management.
• Develop, test, deploy, and maintain scalable software solutions throughout the SDLC.
• Troubleshoot data pipeline issues and implement timely resolutions.
• Conduct software testing and validate data processing solutions before deployment.
• Research emerging technologies and recommend innovative data engineering solutions.
• Participate in Agile/Scrum ceremonies and collaborate with cross-functional teams.
• Provide regular status updates and contribute to continuous improvement initiatives.

Required Qualifications
• Experience designing and developing scalable enterprise data pipelines.
• Strong understanding of the Software Development Life Cycle (SDLC).
• Strong understanding of data warehousing concepts and architecture.
• Experience building ETL pipelines using Informatica IICS, Alteryx, or similar ETL tools.
• Experience developing high-volume cloud-based data processing workflows.
• Experience delivering enterprise data warehouse and business intelligence solutions.
• Hands-on experience with Snowflake.
• Experience implementing streaming data solutions using Apache Kafka.
• Experience with data cleansing, validation, transformation, and data wrangling.
• Hands-on experience with AWS cloud services including:
• AWS Glue
• AWS Lambda
• Amazon Kinesis
• AWS Lake Formation
• Amazon S3
• Amazon Redshift
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to work independently and within Agile development teams.
• Excellent communication and collaboration skills.

Preferred Qualifications
• Experience with AWS EMR (Spark).
• Experience with Amazon RDS, EC2, Athena, CloudWatch, and CloudTrail.
• Experience developing and consuming APIs.
• Experience with business intelligence platforms such as Tableau, Cognos, or ThoughtSpot.
• Experience working in enterprise-scale cloud data environments.

Mandatory Skills
• AWS Data Engineering
• AWS Glue
• AWS Lambda
• Amazon Kinesis
• AWS Lake Formation
• Amazon S3
• Amazon Redshift
• Snowflake
• Apache Kafka
• ETL Development
• Informatica IICS / Alteryx
• Data Warehousing