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

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.

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 SkillsCloud 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 CertificationsAWS Data Engineering certifications. AWS Solutions Architect Professional.