*Contingent Upon Award
US- Richmond/VA
ABOUT THE ROLE
We are seeking a Database Administrator / Data Engineer with strong experience in migrating on-premises databases to AWS. The candidate will support data platform modernization by assisting with database migration, Python-based data processing, and building AWS data pipelines supporting applications using Amazon RDS and DynamoDB.
Responsible for supporting SQL Server/Cloud BAU operations. supports production stability and performance monitoring by building operational metrics and dashboards for database performance. Develop data quality and performance dashboards to monitor system efficiency and ensure reliable data for reporting and analytics.
The role requires hands-on experience in database migration, data modeling, and AWS data services.
Must Have Skills (Screening Required)
1. On-Prem SQL server to AWS and snowflake source Data Migration experience
• Experience migration/archiving databases from on-premises environments to AWS
• Experience with AWS Database Migration Service(DMS) or similar tools preferred
2. AWS Database Technologies
• Strong experience with:
• Amazon RDS
• DynamoDB
3. Python for Data Processing
• Experience developing Python scripts for data creation, transformation, and data loads
4. Data Pipeline Development
• Experience building AWS-based data pipelines
• Familiarity with services such as:
• S3, Glue, Lambda
5. Data Modeling
• Experience designing logical and physical data models
• Ability to support application teams with schema design
Preferred Skills
• Experience with AWS Schema Conversion Tool (SCT)and data migration service (DMS)
• Experience working with large datasets and ETL pipelines
• Knowledge of data lake architecture
• Experience with PostgreSQL, SQL Server, Dynamo Db
• Experience supporting application data environments
Experience Required
• 5+ years in Database Administration, Data Engineering, or similar role
• 3+ years of AWS and Snowflake experience
Responsibilities
• Support migration of on-prem databases to AWS
• Develop Python scripts for data generation and bulk loads
• Build and maintain AWS-based data pipelines
• Design and support data models
• Support application teams using RDS and DynamoDB
• Assist with data validation, migration testing, and performance tuning
Skills Required
- At least 5 years of on-premises SQL Server to AWS and Snowflake data migration experience
- At least 5 years migrating or archiving databases from on-premises environments to AWS
- At least 5 years of experience with AWS Schema Conversion Tool and AWS Database Migration Service or similar tools
- At least 5 years developing Python scripts for data creation, transformation, and data loads
- At least 5 years building AWS-based data pipelines using Amazon S3, AWS Glue, and AWS Lambda
- At least 5 years supporting application data environments and working with PostgreSQL, SQL Server, and DynamoDB
- At least 5 years using AWS database services including S3, RDS, PostgreSQL, DynamoDB, and Snowflake
- At least 5 years configuring AWS data management practices using AWS Glue, AWS DataZone, AWS Glue Data Catalog, and API Gateway
- At least 5 years using version control tools such as GitHub and AWS CodePipeline
- At least 5 years in database administration, data engineering, or a similar AWS, Snowflake, and SQL Server role
- Experience with large datasets and ETL pipelines
- Knowledge of data lake architecture
- Experience designing logical and physical data models and supporting application schema design
What We Do
Betis Group, Inc. provides information technology products, solutions, and services to public and private-sector organizations, including government, commercial, healthcare, and education clients. The company delivers end-to-end support across systems and software engineering, enterprise IT, cloud platforms, technology deployments, staff augmentation, infrastructure installation and upgrades, and hardware and software sales. It also manages infrastructure and applications, supports secure operations, and helps clients modernize and improve performance.
