Data Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced Senior Data Engineer to support and enhance enterprise business intelligence and analytics environments. This role focuses on designing, building, and maintaining scalable data pipelines and cloud-based data platforms using AWS services. The ideal candidate brings deep hands-on experience with AWS Glue, PySpark, Redshift, and serverless architectures, along with strong SQL and data analysis skills.
This role will collaborate closely with architecture, security, compliance, and development teams to ensure data solutions are performant, secure, and compliant with regulatory requirements., * Design, build, and maintain scalable ETL/ELT pipelines using AWS Glue with PySpark for large-scale data processing
- Develop and support serverless integrations using AWS Lambda for event-driven workflows and system integrations
- Design and optimize Amazon Redshift data warehouse solutions, including:
- Advanced SQL analytics
- Stored procedures
- Performance tuning
- Lead implementation of secure vendor file transfer and ingestion solutions using AWS Transfer Family
- Design and implement database migration and replication pipelines using AWS Database Migration Service (DMS)
- Build and manage workflow orchestration using Apache Airflow or similar orchestration tools
- Analyze data quality, transformation logic, and pipeline performance using SQL and data analysis techniques
- Troubleshoot and resolve production data pipeline and integration issues across AWS services
- Provide technical guidance to development team members on:
- AWS best practices
- Cost optimization
- Performance optimization
- Partner with enterprise architecture, security, and compliance teams to ensure SOX and regulatory compliance
Requirements
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or equivalent practical experience
- 7+ years of experience building enterprise data platforms or data engineering solutions
- 5+ years of hands-on experience with AWS cloud services
- Strong hands-on experience with AWS Glue and PySpark for ETL processing
- Experience developing serverless applications using AWS Lambda
- Deep expertise with Amazon Redshift, including performance tuning and advanced SQL
- Experience with workflow orchestration tools such as Apache Airflow
- Experience implementing secure vendor integrations using AWS Transfer Family
- Experience designing and supporting data migration and replication pipelines using AWS DMS
- Advanced SQL skills and experience analyzing complex datasets
- Knowledge of AWS security, encryption, IAM policies, and compliance considerations
- Strong troubleshooting, problem-solving, and analytical skills
Preferred Qualifications
- Experience working in financial services or other regulated environments
- Experience supporting enterprise BI or analytics platforms
- Strong communication skills and ability to work cross-functionally with technical and non-technical teams
Benefits & conditions
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