SQL DBA and Data Transformation Expert

About the role

We are seeking a SQL DBA & Data Transformation Expert to manage database performance, security, and reliability while driving data integration, transformation, and reporting initiatives. This hybrid role combines database administration in AWS with data engineering and analytics, ensuring accurate data movement across systems and delivering actionable business insights.

Requirements-

Must have

• Experience. 7 to 10 years of hands-on work with relational databases in production, including at least 3+ years with direct database administration responsibility and at least three years building data integration, transformation, or migration pipelines. Those years can overlap.
• SQL depth. Expert level SQL. You write complex analytical queries without reaching for a tool, you read execution plans fluently, and you know how to make a slow query fast and a fragile schema durable. Deep experience with PostgreSQL is strongly preferred. Experience with SQL Server, MySQL, or Oracle is useful, particularly since legacy EMR migrations will put you in front of all of them.
• AWS database services. Production experience administering databases on AWS, including Amazon RDS and Aurora. Familiarity with the surrounding services that matter to a DBA: IAM, KMS, CloudWatch, Secrets Manager, S3, and the networking model that governs who can reach the database.
• Data transformation tooling. Hands-on experience with ETL and ELT tools and frameworks such as AWS Glue, dbt, Apache Airflow, or equivalent, and with scripting the parts those tools do not cover, typically in Python.
• Data modeling. Strong understanding of relational and dimensional modeling, normalization and when to break it, and the tradeoffs between transactional and analytical schemas.
• Analysis and reporting. Demonstrated ability to take a business question, find the data that answers it, and present the answer in a form a non-technical operator can use. Experience with a reporting or BI layer such as Amazon QuickSight, Metabase, Power BI, or Tableau.
• AI tool fluency. Comfort using AI tools as part of your daily workflow, Anthropic Claude in particular. We use AI throughout our process, and you should be working with it, not around it.
• Education. A four-year college degree in computer science, information systems, or a related field from an accredited institution, or equivalent practical experience.