Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Seattle, WA, United States
Posted
Yesterday
DynamoDBMongoDBSQLSQL ServerAWSETLNumPyCassandraKafkaPandasPythonStakeholder Management
Job Description
Required Skills
✅ AWS Glue
✅ AWS DMS (Database Migration Service)
✅ CDC (Change Data Capture)
✅ Python / PySpark
✅ Kafka or SNS/SQS
✅ Data Lake Architecture
✅ SQL & Database Design
✅ AWS CloudWatch
✅ AWS CloudTrail
✅ Data Integration & ETL Development
Preferred Skills
- AWS IAM
- Amazon EKS
- EventBridge
- MongoDB, Cassandra, DynamoDB
- Data Migration & Modernization Projects
- Real-Time Streaming Architectures
- CI/CD for Data Platforms
Key Responsibilities
- Design, develop, and maintain scalable data pipelines in AWS using AWS Glue, Python, and PySpark.
- Build robust data ingestion frameworks to collect and process data from multiple on-premises and cloud-based sources.
- Implement Change Data Capture (CDC) solutions for near real-time data synchronization and replication.
- Utilize AWS Database Migration Service (AWS DMS) to migrate and replicate data across enterprise systems with minimal downtime.
- Design and implement event-driven architectures using Kafka, Amazon SNS, Amazon SQS, and EventBridge.
- Develop cloud-native data processing solutions supporting high availability, scalability, and performance.
- Build, optimize, and maintain enterprise Data Lake solutions.
- Monitor and troubleshoot data workflows using AWS CloudWatch and AWS CloudTrail.
- Develop efficient Python-based data processing applications leveraging libraries such as Pandas and NumPy.
- Work with relational and NoSQL databases including SQL Server, DynamoDB, MongoDB, and Cassandra.
- Support migration and modernization of legacy data pipelines into AWS-based architectures.
- Collaborate with business stakeholders, application owners, and data teams to understand data architecture, business requirements, and analytics needs.
- Document data models, ETL processes, data flows, and target-state architectures.
- Drive continuous improvements in data quality, platform performance, security, and operational efficiency.
Qualifications
- 7+ years of experience in Data Engineering and Data Integration.
- Hands-on experience with AWS-based data platforms and cloud-native applications.
- Strong expertise in Python and PySpark development.
- Experience implementing CDC and real-time data streaming solutions.
- Strong understanding of data modeling, SQL optimization, and enterprise data architecture.
- Excellent communication and stakeholder management skills.
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