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Open nowPosted 47 days ago

Talent Acquisition Lead

Koantek34 open roles

Where
Mumbai, Maharashtra, India
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Your applicationOpen nowTalent Acquisition LeadKoantek · Mumbai, Maharashtra, India

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Koantek's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 47 days ago

The posting

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 & 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.

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    The review screen in CV Rocket: how each CV was read, round by round.

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