Data Engineering Manager (Snowflake expert)

Mitchell Martin Inc.; Charlotte (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

Mitchell Martin Inc. is seeking a Data Engineering Manager to own our enterprise Snowflake data platform and lead a high-performing team in Charlotte, NC.

You will set the technical vision and enforce standards across ingestion through consumption, mentoring engineers and driving architectural decisions. You will partner with analytics, infrastructure, andInfoSec teams to deliver scalable, secure, and cost-efficient data solutions while shaping our data strategy and toolset.

Qualifications

• Experience owning enterprise Snowflake data platforms.
• Strong leadership and mentoring capabilities.
• Cross-functional collaboration with analytics and security teams.

Responsibilities

• Lead, mentor, and grow a team of data engineers and architects.
• Provide hands-on guidance through code reviews, architecture sessions, and 1:1s.
• Foster a culture of excellence, innovation, and continuous improvement.
• Own end-to-end Snowflake platform architecture, design, and stewardship.
• Set enterprise RBAC, row-level security, data sharing, lifecycle management.
• Define scalable ingestion/transformation/consumption patterns using Fivetran and dbt.
• Evaluate Snowflake capabilities and third-party tools.
• Oversee reliability and cost optimization, including monitoring and tuning.
• Partner with InfoSec to implement security controls and regulatory compliance.
• Collaborate with stakeholders to align the platform roadmap with enterprise priorities.
• Contribute to long-term cloud data platform, AI, and analytics strategy.
• Identify and drive process and tooling improvements for efficiency.

Tools

Snowflake

dbt

Fivetran

Job description

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.