Data Architect

NEP Group•Pittsburgh, PA

22h•Hybrid

About The Position

NEP Group is a global leader in live sports, entertainment, and media solutions, supporting the worlds most high-profile events and productions. As our data ecosystem continues to grow, we are investing in a modern, scalable data platform to power analytics, AI, and smarter decision-making across the business. The Opportunity Were looking for an experienced Data Architect to own the vision, design, and governance of NEPs enterprise data platform. In this role, youll define how data flows across the organizationensuring it is secure, scalable, performant, and aligned with business goals. We are seeking a person with 8+ years of experience in data architecture. Youll work closely with engineering, analytics, data science, and business stakeholders to shape end-to-end data architecture using Snowflake, Databricks, and dbt , while setting standards and best practices that enable everything from BI to advanced AI/ML. Preference is for this to be a hybrid role in Pittsburgh, but we are open to fully remote candidates in Eastern or Central time zones.

Requirements

Bachelors degree in Computer Science, IT, or related field (Masters preferred) with 8+ years of data architecture experience
Hands-on expertise with Snowflake, Databricks, and dbt in enterprise data environments
Strong knowledge of data modeling, security frameworks, and data governance best practices
Experience designing scalable, performant, and cost-efficient cloud data architectures , including distributed processing (e.g., Spark)
Familiarity with modern data governance, quality, and lineage tools (e.g., Unity Catalog or equivalent)
Proven ability to define and enforce standards for ingestion, transformation, and validation pipelines

Responsibilities

Own the overall architecture, design, and governance of NEPs data platform
Design, document, and evolve the end-to-end data architecture , from ingestion to consumption
Define data models, integration patterns, and architectural standards
Ensure platform scalability, performance, security, and compliance
Partner with data engineers and data scientists to optimize data models and pipelines
Translate business requirements into practical, future-proof data solutions
Define and enforce data governance, quality, and lineage best practices
Evaluate and recommend new tools and technologies to improve data management and analytics
Communicate complex technical concepts clearly to both technical and non-technical audiences