Senior Talent Acquisition Specialist

Koantek; Mumbai; On-site; INR 2,800,000 - 3,800,000; Full time

Job summary

Koantek is seeking a strategic, research-driven Senior Talent Acquisition Specialist to drive targeted end-to-end recruitment for niche Data, AI, and Data Science roles in Mumbai. The role emphasizes proactive headhunting, talent mapping, and building robust pipelines to engage passive candidates in non-volume hiring scenarios.

The role covers full lifecycle hiring across Data Engineering, Data Science, ML, GenAI, MLOps, Data Architecture, and Analytics, with a focus on partnering with CTOs and

Qualifications

• 6-8 years of experience in technical recruitment hiring niche Data/AI talent.
• Demonstrated expertise in headhunting, passive outreach, market mapping and structured search.
• MBA or postgraduate degree in HR or business management is required.

Responsibilities

• Lead end-to-end recruitment across Data Engineering, Data Science, ML, GenAI, MLOps, and Analytics.
• Translate complex technical requirements into targeted sourcing strategies and build robust talent pipelines.
• Engage passive candidates through proactive headhunting and relationship building.
• Provide market intelligence on compensation trends, skills availability, and competitor hiring patterns.
• Partner with CTOs, CIOs, and engineering leaders to calibrate requirements and hiring strategies.
• Articulate technology opportunities to candidates and manage end-to-end offer discussions.

Skills

Head hunting

Market mapping

Passive candidate outreach

Sourcing strategies

Technical recruitment

Education

MBA or Postgraduate degree in HR or Business Management

Tools

LinkedIn Recruiter

Boolean search

GitHub

Job description

We are looking for a strategic, research-driven Senior Talent AcquisitionSpecialist 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.