Data AI Engineer (CLT)

Matlen Silver; Charlotte, Northern (NC, KY); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Matlen Silver seeks a senior Data Engineer to design, build, and scale data integration platforms and AI-enabled solutions in cloud environments. You will own real-time, near real-time, and batch pipelines, with a focus on governance and security in regulated settings.

Collaborating with globally distributed teams, you’ll deploy production-grade data solutions using Spark, Hadoop, Scala, and Python, integrating AI/GenAI components while upholding operational excellence in Charlotte, NC.

Qualifications

• 8+ years of experience in data engineering, software engineering, AI/ML engineering, or related roles.
• Strong programming in Scala or Python and SQL; enterprise-grade data solutions.
• Experience designing, deploying data integration solutions with Informatica, Hadoop, Oracle, and related tech.

Responsibilities

• Design, develop, and implement scalable data integration platforms and AI-enabled solutions.
• Build real-time, near real-time, and batch data processing pipelines.
• Collaborate with global teams to ensure security, compliance, and operational excellence.
• Leverage LLMs, GenAI, RAG architectures, and vector databases in production workloads.
• Coordinate with deployment and production support for testing and release.

Skills

Scala

Python

SQL

LLMs

RAG

Vector databases

MLOps

Kubernetes

OpenShift

Spark

Hive

Kafka

API integration

Agile

Leadership

Cloud platforms

Tools

OpenShift

Kubernetes

Spark

Hive

Kafka

Job description

Design, develop, and implement scalable data integration platforms and AI-enabled solutions leveraging modern cloud, data, and machine learning technologies. This role requires strong expertise in data engineering, real-time and batch processing, AI/GenAI application development, and deployment of models within containerized environments. The engineer will collaborate with global teams to build resilient data pipelines, AI-driven solutions, and production-grade platforms while ensuring security, compliance, scalability, and operational excellence in highly regulated environments.

• 8+ years of experience in Data Engineering, Software Engineering, AI/ML Engineering, or related technology roles.
• Strong programming skills in Scala or Python and SQL, with experience building enterprise-grade applications and data solutions.
• Hands-on experience designing, developing, and deploying data integration solutions using Informatica, Hadoop, Oracle, and related technologies.
• Experience building AI/GenAI applications utilizing LLMs, RAG architectures, vector databases, and model inferencing frameworks.
• Experience developing and supporting real-time, near real-time, and batch processing solutions.
• Understanding of software engineering best practices, design patterns, testing, and production support processes.
• Strong analytical, problem-solving, and quantitative skills with the ability to quickly learn new technologies and platforms.
• Experience working within Agile delivery teams and collaborating across multiple business and technology organizations.
• Ability to coordinate with development, deployment, and production support teams to ensure successful delivery into testing and production environments.
• Strong communication, presentation, stakeholder management, and leadership skills.
• Experience working with globally distributed teams across multiple time zones.
• Experience with AI/ML concepts, Generative AI, Large Language Models (LLMs), Agentic AI, and Prompt Engineering.
• Retrieval Augmented Generation (RAG) architecture and vector databases.
• Understanding of MLOps, model monitoring, and AI governance.
• Data integration and ETL/ELT development using Informatica, Hadoop ecosystem, and Oracle SQL.
• Experience with distributed data processing technologies such as Spark and Hive.
• Design and implementation of real-time, near real-time, and batch data pipelines.
• Data modeling, metadata management, data quality, and data governance concepts.
• Experience with API integration and event-driven architectures (Kafka preferred).
• OpenShift/Kubernetes container technologies.
• CI/CD pipelines, DevOps practices, and Infrastructure as Code.