Senior Manager – Data Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the primary expert on Snowflake architecture, optimizing performance, managing costs, and ensuring security (RBAC, data masking, network policies).

• Create and uphold a scalable, thoroughly documented warehouse structure that includes standards for databases, schemas, and object hierarchies.

• Propel the adoption of Snowflake features such as dynamic tables, Snowpark, data sharing, and other innovative capabilities.

• Oversee the dbt project from start to finish: including modeling conventions, testing strategies, documentation standards, and CI/CD integration.

• Implement and uphold a multi-layered modeling strategy (staging → intermediate → marts) that downstream teams can trust and utilize independently.

• Direct the design and execution of data pipelines on Azure, particularly using Azure Data Factory.

• Guarantee reliable, monitored data transfer from source systems into Snowflake, with clear Service Level Agreements (SLAs) and alert systems.

• Manage, mentor, and develop a team of data engineers by conducting regular one-on-ones, establishing performance objectives, and fostering a culture of engineering excellence.

• Oversee the hiring, onboarding, and professional growth of the data engineering team.

• Convert business requirements from stakeholders into well-defined, prioritized engineering tasks.

• Define and implement best practices for ETL/ELT across the organization, alongside naming conventions and code review standards.

• Advocate for data quality, observability (e.g., dbt tests), and data lineage throughout the platform.

• Identify potential areas for improving data processes proactively and lead initiatives to enact these enhancements.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline.

• Over 7 years of experience in data engineering, including a minimum of 2 years in a leadership or management position.

• Extensive, hands-on Snowflake expertise — capable of designing warehouse architectures, optimizing query performance, managing costs, and applying enterprise security measures.

• Proficient in dbt: experienced in building and managing large-scale dbt projects and able to communicate best practices effectively.

• Practical experience with Azure Data Factory.

• Strong SQL skills and proficiency in Python for developing and automating data pipelines.

• Demonstrated ability to lead and nurture a small team while maintaining technical involvement.

• Excellent communication skills to translate complex data concepts for non-technical stakeholders and contribute to strategic planning discussions.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• A dynamic and collaborative work environment.