Data Engineer — Charlotte Metro

Semantic Layer Analyst / Data Engineer – Semantic Modeling

Location: Malvern, PA / Charlotte, NC / Dallas, TX

Hybrid: Tuesday–Thursday onsite; Monday and Friday remote

Experience: Mid-level, preferably 5–8 years of relevant experience

Position Summary

We are seeking a Data Engineer or Analytics Engineer with strong experience in semantic data modeling, cloud data platforms, and enterprise data consumption.

The role focuses on building and maintaining semantic data structures that allow business users, analytics platforms, and AI-enabled applications to access and consume data consistently.

The ideal candidate will have hands-on experience with Databricks, AWS, Amazon Redshift, Snowflake, or comparable cloud data platforms, along with an understanding of how data is modeled and made available for business consumption.

Candidates do not need to have held the exact title of Semantic Layer Analyst. We are open to Data Engineers, Analytics Engineers, and Data Modelers who have performed relevant semantic modeling responsibilities.

Key Responsibilities

• Design, develop, and maintain semantic data models that support enterprise analytics and business data consumption.

• Translate business requirements into reusable data models, standardized metrics, and semantic definitions.

• Work with cloud data platforms such as Databricks, Snowflake, Amazon Redshift, and AWS.

• Build and maintain logical relationships between data entities, business measures, and analytical datasets.

• Collaborate with Data Engineers, Data Stewards, and business stakeholders to ensure consistent data definitions.

• Support data integration, transformation, and preparation for downstream consumption.

• Improve data accessibility and usability for business intelligence, reporting, and analytical applications.

• Ensure data models are consistent with enterprise governance and data quality standards.

• Support AI-enabled data consumption and analytical use cases.

• Investigate and resolve issues involving data modeling, semantic definitions, and data consumption.

Required Skills and Experience

• Hands-on experience in Data Engineering, Analytics Engineering, Data Modeling, or Semantic Layer Development.

• Strong SQL skills and experience with data modeling concepts.

• Practical experience with Databricks, Snowflake, Amazon Redshift, or AWS data technologies.

• Understanding of semantic layers, semantic models, business metrics, and analytical data consumption.

• Experience developing reusable data structures for reporting, analytics, or business applications.

• Knowledge of dimensional modeling, data transformations, and cloud data architectures.

• Some exposure to AI/ML, AI-enabled analytics, or AI-related data consumption.

• Ability to translate business data requirements into technical models.

• Financial services or banking experience preferred.

Keys to success:

• Candidates must demonstrate actual experience with semantic modeling or creating data structures for analytical consumption.

• A Data Engineer who has only worked on ETL pipelines, ingestion, or infrastructure without semantic modeling experience is not an ideal fit.

• Look for candidates who understand both the technical data platforms and how business users consume the data.

• Prioritizing local candidates with relevant cloud platform experience and some AI exposure.

# Data Engineer #Analytics Engineer #Semantic Data Modeler #Data Modeling Engineer

• # BI Engineer #Data Engineer – Databricks / Snowflake