Role Overview

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.

Advanced Sourcing & Intelligence
- 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.
- AI & Machine Learning: Machine Learning, Deep Learning, Generative AI/LLMs, NLP, Computer Vision, MLOps.
- Cloud & Contemporary 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.

📌 Talent Acquisition Lead (Navi Mumbai)
🏢 Koantek
📍 Navi Mumbai