Talent Acquisition Lead

Koantek; Mumbai; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Koantek in Mumbai seeks a strategic Talent Acquisition Lead to drive end-to-end recruitment for niche Data, AI, and Data Science roles. This role requires deep technical recruitment expertise, proactive headhunting, and talent mapping to engage passive candidates in non-volume hiring scenarios.

You will partner with CTOs and engineering leaders, translate complex tech requirements into targeted sourcing strategies, build robust talent pipelines, manage offers and negotiations, and provide market

Qualifications

• 6–8 years of experience in technical recruitment for niche Data, AI and Data Science roles.
• Proven ability to headhunt passive candidates and map talent across geographies and tech stacks.
• MBA or postgraduate degree in HR or business management, strong communication and stakeholder skills.

Responsibilities

• End-to-end talent acquisition across Data Engineering, Data Science, ML, GenAI, and related areas.
• Translate complex requirements into targeted sourcing strategies and build robust pipelines.
• Lead proactive headhunting, engage passive candidates, and manage end-to-end offers and negotiations.
• Provide market intelligence on salaries, trends, and competitor hiring patterns to leadership.
• Partner with CTOs and engineering leaders to calibrate hiring strategies and roadmaps.

Skills

Full lifecycle hiring

Head hunting

Talent mapping

LinkedIn Recruiter

GitHub

Boolean search

Sourcing strategy

Stakeholder management

Education

MBA or Postgraduate HR

Business Management

Tools

LinkedIn Recruiter

GitHub

Boolean/X-ray search

Job description

We are looking for a strategic, research-driven Talent Acquisition Lead to drive targeted end-to-end recruitment for niche Data, AI, and Data Science roles. This role requires deep technical recruitment expertise, proactive headhunting, and talent mapping to engage passive candidates in non-volume hiring scenarios.

Key Responsibilities

End-to-End Talent Acquisition

Full Lifecycle Hiring: Manage end-to-end recruitment across Data Engineering, Data Science, Machine Learning, Generative AI, MLOps, Data Architecture, Cloud Data, and Advanced Analytics.

Sourcing Strategy: Translate complex technical job requirements into targeted sourcing strategies and build robust talent pipelines for immediate and future needs.

Headhunting & Targeted Search

Proactive Search: Personally lead targeted headhunting efforts and map talent pools across companies, geographies, and technology stacks to engage high-caliber passive candidates.

Relationship Building: Employ creative engagement approaches and foster long-term relationships with niche technical professionals.

Digital Sourcing: Utilize LinkedIn Recruiter, GitHub, Boolean/X-ray search, professional communities, and digital channels to identify technical talent.

Market Intelligence: Provide leadership with actionable insights on market trends, skills availability, compensation standards, competitor hiring patterns, and talent concentrations.

Stakeholder & Candidate Management

Strategic Partnership: Partner closely with CTOs, CIOs, and engineering leaders as a trusted advisor to calibrate requirements and set hiring strategies.

Offer Management: Articulate complex technology opportunities to candidates and effectively manage end-to-end offer discussions and negotiations.

Technical Focus Areas

Candidates must possess functional familiarity across the following technical domains to conduct intelligent screenings:

Data & Engineering: Big Data, Data Warehousing, Data Architecture, Databricks, Snowflake, ETL/ELT, SQL.

Cloud & Modern Stack: AWS/Azure/GCP, Data Lakes/Lakehouse, Data Governance.

Data Science & Analytics: Applied/ML/Decision Scientists, Product Analytics, Advanced Analytics, Business Intelligence.

Key Requirements & Differentiators

Experience: 6–8 years of experience in technical recruitment with a proven track record of hiring niche Data, AI, and Data Science talent.

Search Expertise: Demonstrated expertise in headhunting, passive candidate outreach, LinkedIn Recruiter, Boolean search, and structured market mapping.

Technical Depth: Ability to differentiate subtle skill sets (e.g., Data Engineer vs. ML Engineer vs. GenAI Specialist) beyond simple keyword matching.

Network: Strong network within top technology firms, AI companies, product organizations, or specialized consulting practices.

Soft Skills: Exceptional communication, influencing, executive presence, and stakeholder management capabilities.

Education: MBA or Postgraduate degree in HR or Business Management.