Data Engineering Manager (Snowflake expert)

One of our clients, is looking for a Data Engineering Manager (Snowflake/dbt)

Location: Charlotte, NC

Position Type: Full Time

Seeking a Data Engineering Manager to own our enterprise Snowflake data platform and lead a high-performing data engineering team. In this hands-on leadership role, you will set the technical vision, enforce standards and best practices, and build the Central Data Platform from ingestion through consumption. You will combine deep Snowflake expertise with strong people leadership — mentoring engineers, driving architectural decisions, and partnering cross-functionally to deliver scalable, secure, and cost-efficient data solutions. This is a high-impact position where you will shape our data strategy and influence tools, patterns, and capabilities across the organization.

Key Responsibilities:

• Technical Leadership & Team Management: Lead, mentor, and grow a team of data engineers and architects. Provide hands-on guidance through code reviews, architecture sessions, workshops, and 1:1s. Foster a culture of excellence, innovation, and continuous improvement.
• Platform Ownership: Own end-to-end architecture, design, implementation, and stewardship of the Snowflake platform (administration, data modeling, performance, cost optimization, security). Establish and evangelize enterprise standards for RBAC, row-level security, data sharing, lifecycle management, cloning, and AI features.
• Design Patterns & Integrations: Define and document scalable implementation patterns for ingestion (Fivetran), transformation and consumption layers using (dbt). Evaluate and drive adoption of new Snowflake capabilities and third-party tools.
• Performance, Reliability & Cost Optimization: Oversee monitoring, tuning (warehouse sizing, clustering, materializations), troubleshooting, and root-cause analysis to ensure reliability and efficiency at scale.
• Security & Compliance: Partner with InfoSec to implement and maintain advanced security controls (dynamic masking, encryption, auditing, RLS) while meeting regulatory requirements.
• Strategic Planning & Collaboration: Work with data, analytics, infrastructure, and business stakeholders to align the platform roadmap with enterprise priorities. Contribute to long-term strategy around cloud data platforms, AI, and analytics.
• Continuous Improvement: Identify and drive process, tooling, and platform enhancements that deliver measurable efficiency gains.

Thanks,

Priya

[email protected]