Data Architect

Counterpoint Labs, Inc.; Charlotte (NC); On-site; USD 120,000 - 150,000; Full time

Job summary

A technology company in Charlotte, NC, is seeking a hands-on Data Architect to define, build, and own the data foundation for operational, AI, and client-facing solutions. This role involves designing scalable data stores, building data pipelines, and ensuring data quality and performance. Ideal candidates will have experience with modern data platforms and cloud technologies. A strong sense of ownership and pragmatic mindset is essential.

Qualifications

• Experience designing and building modern data platforms.
• Hands-on experience with cloud data stacks (e.g., AWS, GCP, Azure).
• Strong understanding of data modeling, ETL/ELT, and streaming data.

Responsibilities

• Define data architecture standards across operational, vision, and AI systems.
• Design and build scalable data stores (cloud and edge as required).
• Build data ingestion, transformation, and processing pipelines.

Skills

Data architecture standards

Scalable data store design

Data ingestion

Cloud data stacks (AWS, GCP, Azure)

Data modeling

Job description

Define, build, and own the data foundation that powers Counterpoint Labs' operational, AI, and client-facing solutions. A hands‑on role designing and implementing scalable data stores and pipelines.

Role Overview

We are looking for a hands‑on Data Architect who will define, build, and own the data foundation that powers Counterpoint Labs' operational, AI, and client-facing solutions. This role is not theoretical or governance‑only. You will personally design and implement how data is stored, defined, moved, and processed across operational systems, vision platforms, and AI pipelines. You will also build and maintain the core data stores used internally and in client environments.

What You Will Do

• Define data architecture standards across operational, vision, and AI systems
• Design and build scalable data stores (cloud and edge as required)
• Define canonical data models for manufacturing, supply chain, and operations
• Build data ingestion, transformation, and processing pipelines
• Ensure data quality, reliability, and performance
• Partner closely with AI, vision, and software engineers to enable downstream use cases
• Make pragmatic architecture decisions balancing speed, cost, and scalability

What Success Looks Like

• A reliable, well‑structured data foundation that supports AI and analytics at scale
• Fast, trusted access to operational data for internal teams and clients
• Clear data definitions that eliminate ambiguity across systems
• Architecture that scales from pilots to production deployments

Ideal Candidate Profile

• Experience designing and building modern data platforms
• Hands‑on experience with cloud data stacks (e.g., AWS, GCP, Azure)
• Strong understanding of data modeling, ETL/ELT, and streaming data
• Experience working with operational or industrial data is a strong plus

Personal Traits We Value

• Builder mindset
• Pragmatic and outcome‑focused
• Comfortable operating without heavy process
• Strong sense of ownership