Technical Data Architect

Quantiphi; Charlotte (NC); Hybrid; USD 120,000 - 190,000; Full time

Job summary

Quantiphi in Charlotte, NC is seeking an experienced Technical Data Architect to lead design, architecture, and delivery of large-scale data platforms. The role blends hands-on data engineering with leadership of distributed teams in hybrid onsite/offshore settings.

You will define scalable data architectures, build batch and streaming pipelines, optimize performance and cost, and champion DataOps, CI/CD, and governance.

Qualifications

• Experience designing scalable data architectures for large-scale platforms.
• Strong command of SQL and data modeling.
• Experience leading complex data projects and teams.

Responsibilities

• Define and implement scalable Data Architecture strategies for enterprise data platforms.
• Develop data models aligned with business requirements.
• Establish standards for data structures, data integration, metadata, data quality, and governance.
• Oversee high-volume batch data pipelines and distributed processing solutions.
• Architect scalable ETL/ELT frameworks for structured data.
• Design and optimize real-time streaming and event-driven data ingestion.
• Architect cloud-based data warehouse/lakehouse architectures.
• Establish DataOps practices for CI/CD and observability.

Skills

Batch ETL/ELT Pipelines

Distributed Data Processing

Data Ingestion Frameworks

Cloud Data Warehousing/Lakehouse

SQL Tuning/Performance

Workflow Orchestration

CI/CD & DataOps

Data Quality & Observability

Agentic AI / Generative AI Data

Vector Databases & Vector Search

Job description

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients.

Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

• 21 Google Cloud Partner of the Year awards in the past 10 years
• 3 AWS AI/ML Partner of the Year awards
• 3 NVIDIA Partner of the Year awards
• 3 Snowflake Partner of the Year awards
• Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

We are also proud to be certified as a Great Place to Work—reflecting our commitment to our people and our culture.

Job Description: Technical Data Architect

Position Overview

We are looking for an experienced Technical Data Architect to lead the design, architecture, and delivery of large-scale data platforms and solutions. The ideal candidate combines strong hands-on expertise across modern data engineering and architecture with proven experience managing complex projects, leading distributed teams, and driving delivery through effective processes, motivation, and goal-oriented execution.

This role requires a technology leader and problem solver who can work closely with clients, business stakeholders, architects, engineering teams, and offshore/nearshore teams to translate business requirements into scalable, secure, high-performance data solutions.

The candidate should demonstrate proactiveness, ownership, adaptability, learning agility, and strong cultural alignment, with the ability to operate effectively in client-facing and hybrid onsite/offshore environments.

Key Responsibilities :

• Define and implement scalable Data Architecture strategies for enterprise data platforms.
• Develop conceptual, logical, and physical data models aligned with business and technical requirements.
• Establish standards for data structures, data integration, metadata, data quality, and governance.
• Evaluate architectural trade-offs involving scalability, performance, cost, security, and maintainability.
• Provide technical leadership across large and complex data transformation initiatives.
• Design and oversee high-volume batch data pipelines and distributed data processing solutions.
• Architect scalable ETL/ELT frameworks for structured and semi-structured data.
• Optimize distributed processing workloads for performance, reliability, and cost.
• Establish reusable engineering patterns, frameworks, and standards for data pipelines.
• Architect real-time streaming and event-driven data ingestion solutions.
• Design reliable, scalable architectures for high-throughput and low-latency data processing.
• Address challenges around data ordering, latency, fault tolerance, replayability, and exactly-once/at-least-once processing.
• Define appropriate patterns for integrating streaming data with analytical and operational platforms.
• Design and optimize cloud-based data warehouse/lakehouse architectures.
• Develop strategies for data partitioning, clustering, storage optimization, workload management, and scalability.
• Perform advanced SQL tuning and query optimization for large-scale data workloads.
• Monitor platform performance and identify opportunities for cost and resource optimization.
• Design robust workflow orchestration frameworks for complex data pipelines.
• Establish dependency management, scheduling, retry, recovery, monitoring, and alerting strategies.
• Ensure pipelines are observable, maintainable, and resilient across development and production environments.
• Establish and promote CI/CD and DataOps practices for data engineering and analytics platforms.
• Implement automated testing, deployment, validation, monitoring, and rollback processes.
• Define engineering standards for version control, infrastructure/configuration management, release management, and environment promotion.
• Drive automation to improve delivery velocity, quality, and operational reliability.
• Evaluate and architect modern data solutions supporting Generative AI and Agentic AI use cases.
• Design data architectures supporting RAG, semantic search, embeddings, knowledge retrieval, and AI agents.
• Work with vector databases/vector search technologies and integrate them with enterprise data platforms.
• Define strategies for data ingestion, chunking, embedding generation, metadata management, retrieval, and evaluation.
• Identify opportunities to leverage AI to improve data engineering, analytics, and business processes.

Required Experience & Technical Competencies

Core Technical Areas :

Strong experience in several/all of the following:

• Batch ETL/ELT Pipelines
• Distributed Data Processing
• Data Ingestion Frameworks
• Cloud Data Warehousing / Lakehouse Architecture
• Advanced SQL & Query Performance Tuning
• Workflow Orchestration
• CI/CD & DataOps
• Data Quality, Observability & Reliability
• Agentic AI / Generative AI Data Architecture
• Vector Databases & Vector Search
• RAG / Semantic Retrieval Architectures

Leadership & Delivery :

• Proven experience leading large, complex data projects.
• Experience coordinating multiple engineering teams and stakeholders.
• Experience leading offshore and/or nearshore teams.
• Strong project delivery and execution skills.
• Excellent problem-solving and decision-making capabilities.
• Strong communication and stakeholder-management skills.
• Ability to operate at both strategic architecture and hands‑on technical levels.

What’s in it for YOU at Quantiphi?

• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.
• Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
• Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
• Stay ahead of the curve by gaining hands‑on experience with cutting‑edge AI, ML, data, and cloud technologies while continuously upskilling.