Data Engineering Manager

The Intersect Group; Greenville (SC); On-site; USD 150,000 - 190,000; Full time

Job summary

The Intersect Group in Greenville, SC seeks a Data Engineering & Architecture leader to build and scale a high-performing data team. You will design end-to-end data pipelines and drive enterprise data warehousing initiatives to support analytics at scale.

You will mentor engineers, partner with technology and business leaders to translate requirements into scalable solutions, and help implement Data Vault 2.0, Kimball modeling, and lakehouse architectures.

Qualifications

• 7+ years of experience in Data Engineering, Data Warehousing, or related disciplines.
• 3+ years of people leadership or management experience.
• Proven experience building, mentoring, and developing engineering teams.
• Strong expertise designing and supporting enterprise data warehouse solutions.
• Experience with modern orchestration and transformation tools, including dbt and/or Coalesce.

Responsibilities

• Lead, mentor, and develop a team of Data Engineers and technical professionals.
• Foster a collaborative, accountable, and high-performing engineering culture.
• Participate in hiring, onboarding, coaching, performance management, and career development initiatives.
• Partner with technology and business leaders to define and execute data engineering priorities.
• Help mature and scale the Data Engineering function as the organization grows.
• Design, build, and optimize scalable end-to-end data pipelines.
• Lead efforts around enterprise data warehousing and data architecture best practices.
• Implement and maintain modern ELT/ETL frameworks and processes.
• Develop and support dimensional models, business data models, and analytics-ready datasets.
• Establish standards for data quality, governance, lineage, and modeling.
• Create source-to-target mappings and oversee data integration initiatives.
• Drive Data Vault 2.0, Kimball methodology, and modern lakehouse architectures.

Skills

Leadership

Data Warehousing

Data Modeling

Communication

Mentorship

Tools

dbt

Coalesce

Snowflake

Sigma

Cognos

SQL Server

Job description

• Lead, mentor, and develop a team of Data Engineers and technical professionals.
• Foster a collaborative, accountable, and high-performing engineering culture.
• Participate in hiring, onboarding, coaching, performance management, and career development initiatives.
• Partner with technology and business leaders to define and execute data engineering priorities.
• Help mature and scale the Data Engineering function as the organization continues to grow.

Data Engineering & Architecture

• Design, build, and optimize scalable end-to-end data pipelines.
• Lead efforts around enterprise data warehousing and data architecture best practices.
• Implement and maintain modern ELT/ETL frameworks and processes.
• Develop and support dimensional models, business data models, and analytics-ready datasets.
• Establish standards for data quality, governance, lineage, and modeling.
• Create source-to-target mappings and oversee data integration initiatives.
• Drive best practices around Data Vault 2.0, Kimball methodology, and modern lakehouse/data warehouse architectures.
• Collaborate with senior leaders and department stakeholders to understand business needs and data challenges.
• Translate business requirements into scalable technical solutions.
• Support the evolution of the data platform and cloud modernization initiatives.
• Help define long-term data management, governance, and analytics strategies.
• Partner with cross-functional teams to prioritize data engineering initiatives and deliver business value.

Hands-On Technical Contribution

• Remain actively involved in technical design, development, troubleshooting, and delivery.
• Contribute code, review solutions, and support engineering efforts when needed.
• Act as a technical leader and subject matter expert for the team.
• Provide technical guidance and mentorship to Data Engineers.
• Help establish engineering standards, best practices, and development processes.

Required Qualifications

• 7+ years of experience in Data Engineering, Data Warehousing, or related disciplines.
• 3+ years of people leadership or management experience.
• Proven experience building, mentoring, and developing engineering teams.
• Strong expertise designing and supporting enterprise data warehouse solutions.
• Experience with modern orchestration and transformation tools, including:
• dbt and/or Coalesce
• Deep understanding of:
• Data Vault 2.0
• Kimball Methodology
• Dimensional Modeling
• Data Lake architectures
• Data Governance frameworks
• Experience designing and supporting end-to-end data pipelines.
• Experience creating source-to-target mappings and enterprise data models.
• Strong understanding of data architecture principles and best practices.
• Excellent communication skills with the ability to engage both technical and business stakeholders.
• Demonstrated ability to operate effectively as both a people manager and hands-on technical contributor.

Preferred Qualifications

• Experience working within financial services, banking, or highly regulated industries.
• Experience with Snowflake.
• Experience supporting enterprise analytics platforms and reporting environments.
• Experience with Sigma, Cognos, SQL Server, or similar technologies.
• Exposure to Alteryx.
• Experience leveraging AI-assisted development tools such as Claude Code, Cortex, Copilot, or similar platforms.

Technology Environment

Current and evolving technologies include:

• Snowflake
• dbt
• SQL Server
• Cognos
• Sigma
• Enterprise Data Warehousing Technologies