Data Platform Director—Cloud, AI & Analytics

Vaco by Highspring

Charlotte (NC)

On-site

USD 150,000 - 210,000

Full time

9 days ago

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Job summary

Vaco by Highspring seeks a Director of Data & Analytics to lead the enterprise data platform from design through production, ensuring reliability, data quality, governance, performance, and cost efficiency. You will lead a small technical team and partner with offshore engineers and implementation partners.

The role requires strong data engineering and cloud platform expertise and the ability to communicate with executive stakeholders.

Qualifications

10+ years of experience in data engineering, data platforms, or analytics engineering, including 4+ years leading technical teams.
Experience building and operating enterprise data platforms in production.
Strong experience with Databricks, Snowflake, Azure data services, or comparable modern cloud data platforms.
Strong knowledge of dimensional modeling, Data Vault concepts, SQL, and Python.
Experience designing and supporting data pipelines and integrations across APIs, SaaS applications, files, and other enterprise sources.
Experience with release management, production support, troubleshooting, and performance optimization.
Experience leading distributed/offshore engineering teams and managing implementation partners or vendors.
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience.

Responsibilities

Own the enterprise data platform from roadmap and architecture through production operations.
Lead data platform releases, including design reviews, testing, production readiness, cutover, and stabilization.
Provide hands‑on technical leadership across data models, pipelines, integrations, orchestration, and platform architecture.
Establish engineering standards for testing, source control, deployment, documentation, and reliable data processing.
Own platform reliability, data freshness, incident response, performance optimization, and technical debt.
Establish and maintain data quality, governance, lineage, access controls, and certified datasets.
Lead and develop internal engineers while managing offshore teams, implementation partners, and vendors.
Manage sprint execution, resource planning, vendor deliverables, and overall platform delivery.
Partner with business and executive stakeholders to translate business needs into scalable data solutions.
Help identify and implement practical uses of AI within data engineering and analytics, including AI‑assisted development, automated data quality, and natural‑language access to governed data.