Job Description: • Lead the foundational setup of new data environments, including Snowflake provisioning, SSO configuration, and initial system architecture. • Design, build, and manage scalable data pipelines and ETL/ELT processes to transform raw data into actionable insights. • Support the scaling of engineering teams to handle high volumes of commercial projects while maintaining business continuity during organizational transitions. • Develop and maintain robust DBT data models to support semantic layer build-outs and advanced analytics capabilities. • Partner closely with business leaders and stakeholders to bridge the gap between technical delivery and strategic objectives. • Provide engineering support for custom backend applications, ensuring seamless data integration and reliable exposure to end users. • Establish and enforce best practices for data engineering, architecture, and deployments that can scale across multiple organizations. Requirements: • Proven experience in data engineering with a strong focus on building pipelines, supporting custom applications, and leading deployments. • Hands-on experience with Snowflake and other modern cloud data platforms such as AWS, Azure, or GCP. • Strong technical expertise in DBT for scalable data transformation, modeling, and semantic layer development. • Demonstrated ability to design and build systems from the ground up, not just extend existing infrastructure. • Advanced SQL and Python skills for complex data modeling, performance optimization, and pipeline development. • Ability to balance deep technical expertise with business acumen, confidently navigating complex stakeholder environments. • Comfortable operating in a nimble, mid-size consulting environment where priorities can shift, and adaptability is key. Benefits: Apply tot his job
