AWS Cloud Database Admin/Developer, Senior (DALLAS, TX - HYBRID LOCAL CANDIDATES ONLY)

Job title: AWS Cloud Database Admin/Developer, Senior

Position Type: Contract to hire

Location: Hybrid, Dallas TX

Position Overview

The AWS Cloud Database Admin/Developer, Senior serves as the hands-on engineer for all data engineering efforts, designing, implementing, and optimizing a high-performance data warehouse environment using Snowflake, Databricks, Astronomer, and AWS. This environment serves as the enterprise’s single source of truth and provides a scalable foundation for real-time analytics, data sharing, and AI-driven insights.

This role ensures that the technology data stack is scalable, secure, and aligned with the company’s five-year strategic direction.

Duration: 3–5 months, with the possibility of extension based on performance.

Key Responsibilities

• Infrastructure Automation: Architect robust infrastructure automation pipelines using Terraform, CloudFormation, scripting, Snowpipe, Tasks, and Streams, integrating with tools such as Airbyte, dbt, Fivetran, and AWS.
• Data Modeling: Create and maintain complex data models, including Star Schema, Snowflake Schema, and Data Vault 2.0, tailored for cloud-native performance.
• Stakeholder Collaboration: Collaborate with IT and business stakeholders to curate, document, and implement data lineage, knowledge graphs, data tracing, and compliance KPIs.
• Pipeline Engineering: Architect robust ETL/ELT pipelines using Snowpipe, Tasks, and Streams, integrating with tools such as Airbyte, dbt, Fivetran, and AWS.
• Governance & Security: Implement Role-Based Access Control (RBAC), data masking, and row-level security to support compliance with global standards, including GDPR and HIPAA.
• Performance Tuning: Monitor and optimize query performance and credit consumption to ensure a fast, cost-effective environment. Apply expert-level SQL and deep knowledge of Snowflake features, including Time Travel, Zero-copy Cloning, and Data Sharing.
• Snowflake Reference Designs: Implement reference designs for ETL/ELT pipeline engineering, including integration with AWS platforms.
• Data Governance: Establish architecture and governance standards from data engineering and platform perspectives, and enforce data lineage and data stewardship across all business units.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Management Information Systems, Data Science, Business Administration (MBA), or a related field; or equivalent practical experience.
• 10+ years of IT experience, including experience with Snowflake, dbt, Apache Airflow, Snowflake Cortex, SQL, Fivetran, OpenFlow, AWS data tools, and cloud data engineering.
• 4–6 years of progressive, hands-on development experience in data engineering using Snowflake and AWS, including semantic engineering, data modeling, and data governance.
• 7+ years of data engineering experience, including 3+ years focused specifically on Snowflake and Databricks implementations.

Technical Skills

• Cloud ecosystems and cloud data engineering, with mastery of AWS.

• Snowflake, Snowflake OpenFlow, Snowflake Cortex, Snowpipe, Tasks, and Streams.
• Snowflake features, including Time Travel, Zero-copy Cloning, and Data Sharing.
• Databricks and Astronomer.
• Expert-level SQL, Microsoft SQL, and PostgreSQL.
• dbt, Fivetran, Airbyte, and Apache Airflow.
• AWS data tools, including SageMaker, Glue, Kinesis, and RDS.
• Kafka, microservices, and Amazon EventBridge.
• Terraform, CloudFormation, scripting, and infrastructure automation.
• Python, JavaScript, Scala, Go, and Java.
• Microsoft Power BI and Tableau reporting.
• ETL/ELT pipeline development and data integration patterns.
• Star Schema, Snowflake Schema, and Data Vault 2.0.
• Data standards, IT governance, security architecture, and architecture guidance.
• RBAC, data masking, and row-level security.
• Data lineage, data stewardship, knowledge graphs, data tracing, and compliance KPIs.

Core Competencies

• Design, implement, and optimize scalable, high-performance data warehouse environments.

• Develop cloud-native data models and reliable data pipelines.
• Enable real-time analytics, enterprise data sharing, and AI-driven insights.
• Establish and enforce data engineering, platform architecture, and governance standards.
• Optimize system performance and manage resource consumption.
• Align technical solutions with long-term business objectives.
• Collaborate effectively with IT and business stakeholders.
• Influence stakeholders without formal authority.
• Explain complex data engineering concepts to non-technical audiences.

Required Certifications

• Snowflake Core Pro.
• Snowflake Advanced Architect.

Preferred Certifications

• AWS Data Engineering certifications.
• AWS Solutions Architect Professional.