Ai Data Architect

We Are hiring for below role Work Location: Anywhere in India Job Title: AI Data Architect (Talent Management Focus) In a global enterprise, leaders are racing to transform digitally while demand surges for AI-powered solutions.

Yet, their workforce remains divided—some workstreams handled by all-human project teams, others cobbled together with gig workers or siloed AI tools.

Launching a major client project means weeks of assembling resources, error-prone onboarding, and a constant struggle for oversight.

Our client is dedicated to empowering enterprises to thrive in the age of AI.

They bring common sense AI approach along with innovative technology to transform your AI aspirations into tangible outcomes With its AI-First Talent Platform, these silos vanish.

Hiring managers use the platform to spin up a high stake "pod," instantly combining internal experts, vetted gig analysts, and capable AI agents.

Automated skill-matching ensures the right mix for the job, while governance tools keep every action visible and auditable.

Managers see real-time status and can re-route work at the click of a button if anything stalls.

Experts are guided through upskilling as they partner with AI teammates and have clarity on opportunities.

At our client, they are driving innovation with a Commonsense AI approach — making AI practical, ethical, and results-focused for every business.

Role Overview We are seeking a highly experienced and visionary AI Data Architect with a strong background in talent management and Human Resources (HR) to design, develop, and implement robust data architectures that support our artificial intelligence and machine learning initiatives.

This role will be critical in transforming our platform's data landscape, enabling advanced analytics, predictive modeling, and AI-driven solutions to optimize talent acquisition, development, retention, and overall workforce effectiveness.

Responsibilities Design, develop, and maintain scalable, secure, and efficient data architectures for AI/ML applications, specifically tailored for talent management data.

Collaborate with business leaders, data scientists, and engineering teams to understand data requirements and translate them into technical specifications and data models.

Establish data governance policies, standards, and best practices ensuring data quality, privacy, security, and compliance with relevant regulations (e.g., GDPR, CCPA).

Develop and implement data pipelines for ingesting, transforming, and loading diverse candidate data from various sources (e.g., HRIS, ATS, performance management systems, engagement surveys)Optimize data storage solutions (e.g., lake-house.

data lakes, data warehouses) for performance, cost-efficiency, and accessibility by AI/ML models Lead the selection and integration of new data technologies and tools that enhance our AI capabilities within the talent management domain.

Provide technical leadership and mentorship to data engineers and other team members on data architecture principles and AI best practices Stay abreast of emerging trends and technologies in AI, data architecture, and talent management, recommending innovative solutions to drive business value.

Qualifications Required: Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related quantitative field.6+ years of experience in data architecture, with at least 3-5 years focused on AI/ML data solutions.

Proven experience working with talent management, candidate data, understanding the unique challenges and opportunities within this domain.

Deep expertise in designing and implementing lake houses, data lakes, data warehouses, and data marts using cloud platforms (e.g., AWS, Azure, GCP).

Strong proficiency in database technologies (SQL, No SQL) and data modeling techniques.

Extensive experience with ETL/ELT processes and data pipeline orchestration tools.

Solid understanding of machine learning concepts, algorithms, and their data requirements.

Excellent communication, collaboration, and stakeholder management skills.

Preferred: Experience with specific Talent/HR technology platforms (e.g., Workday, Success Factors, Oracle HCM, Linked In, Dice, Monster etc.).

Familiarity with HR analytics, workforce planning, and talent acquisition metrics.

Knowledge of data visualization tools (e.g., Tableau, Power BI, Looker).

Certifications in cloud data architecture (e.g., GCP, AWS Certified Data Analytics, Azure Data Engineer Associate).

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