Practice Director, Data Architecture

Job not on LinkedIn

🔥 15 minutes ago

🌲 North Carolina – Remote

🌲 North Carolina – Remote

⏰ Full Time

🔴 Lead

🚰 Data Engineer

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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GDT - General Datatech

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1996

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Private Equity Round on 2021-01

Consulting • Healthcare • Logistics

GDT - General Datatech is a global IT solutions provider that specializes in accelerating digitalization and advancing business goals through the transformation and modernization of platforms, networks, and security. The company offers a suite of infrastructure solutions supported by deep expertise and a flexible service delivery model, ensuring that it addresses the most pressing business needs of its clients. GDT stands out through its industry-leading cybersecurity, cloud and data center solutions, enterprise networking, and collaboration offerings. With over 450 certifications worldwide from leading technology providers such as Cisco, HPE, NetApp, and Fortinet, GDT is recognized for its extensive knowledge and ability to solve complex technology challenges, allowing businesses to enhance competitiveness and profitability. Its comprehensive range of services includes managed services, software and support, professional services, and resourcing, all designed to support digital transformation. GDT is committed to maintaining robust partnerships and delivering superior customer experiences.

📋 Description

• Lead discovery, assessment, and architecture engagements for client AI, ML, and LLM initiatives • Build and oversee scalable ingestion, storage, and processing pipelines for structured and unstructured data • Design data flows for training, fine-tuning, RAG, batch scoring, real-time inference, and downstream applications • Define architecture standards for cloud and hybrid environments across AWS, Azure, and Google Cloud Platform • Design data lakes, lakehouses, warehouses, vector databases, feature stores, and supporting platform services • Recommend modular and portable technology patterns that support interoperability and reduce vendor lock-in • Translate business goals and constraints into architecture decisions, roadmaps, implementation plans, and measurable outcomes • Review and validate solution designs for scalability, operability, portability, security, performance, and cost effectiveness • Create architecture artifacts, reference designs, standards, decision records, and implementation guidance • Support presales, scoping, estimates, statements of work, implementation guidance, operational readiness, and knowledge transfer • Build and mature GDT’s Data Practice through reusable delivery assets, methods, accelerators, and technical standards • Contribute to practice enablement, mentoring, partner alignment, thought leadership, and go-to-market capabilities • Work across data science, data engineering, software development, security, infrastructure, and business teams

🎯 Requirements

• Ability to work with clients and account teams to understand functional and non-functional requirements and collaborate across teams to architect, design, validate, and deliver solutions • Strong understanding and practical experience with cloud data and AI services on AWS, Azure, or Google Cloud Platform • Advanced SQL, data modeling, database design, performance, and database security • Python, Apache Spark, Kafka or comparable streaming technologies, and distributed data processing • MLOps tools and practices, including MLflow, Kubeflow, model lifecycle management, CI/CD, and observability • RAG pipelines, embedding generation, vector search, model fine-tuning, evaluation, and inference architectures • Data lakes/lakehouses, data warehouses, vector databases, feature stores, and cloud storage patterns • Data governance, quality, lineage, privacy, security, compliance, and access control • Experience publishing architecture strategies, standards, and guidelines • Mastery in requirements gathering and analysis and translating business needs into technical architectures and roadmaps • Excellent communication, presentation, facilitation, and stakeholder-management skills • Ability to operate independently with a high degree of latitude, handle complex issues, and drive outcomes across multiple stakeholders • Minimum 7+ years of experience in data architecture, data engineering, cloud architecture, analytics platforms, or a related discipline, including enterprise-scale solution design • Experience designing and governing production data platforms and pipelines supporting AI/ML workloads • Experience working directly with clients and account teams to define requirements and translate business outcomes into secure, scalable data architectures and delivery plans • Background in enterprise data architecture and modeling, cloud data platforms, scalable ETL/ELT, batch and streaming architectures, AI/ML data foundations, data governance, and client-facing consulting • Bachelor’s degree in Computer Science, Data Science, Information Systems, Information Technology, Engineering, or a related field; equivalent experience will be considered

🏖️ Benefits

• Career development opportunities • Access to cutting-edge technology • Collaborative environment • People-first, inclusive culture • Meaningful impact and recognition for contributions

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