Talent Acquisition Engineer

1 semana atrás

Curitiba, Paraná, Brasil beBeeData Tempo inteiro R$60.000 - R$100.000
About the Role

We are seeking a highly skilled and experienced engineering professional to join our team as a Talent Advisory & Evaluation Specialist.

This is a fantastic opportunity for someone who has expertise in technical talent evaluation, engineering capability assessments, strategic client advisory, and technical talent pipeline development.

Main Responsibilities
  • Technical Talent Advisory & Evaluation: Conduct in-depth analysis of engineering resumes and portfolios, evaluating candidates' real-world coding experience, scalability considerations, and project relevance against client requirements.
  • Engineering Capability Assessments: Lead structured technical screenings and scenario-based interviews to assess problem-solving skills, depth of systems knowledge, and ability to apply engineering principles.
  • Strategic Client Advisory: Advise CTOs, VPs of Engineering, and Product leaders on engineering talent strategy, translating project requirements and product roadmaps into talent specifications.
  • Technical Talent Pipeline Development: Curate and maintain a network of high-caliber engineers, staying ahead of industry shifts in cloud infrastructure, distributed systems, AI/ML, DevOps, and modern frameworks.
Requirements
  • A bachelor's degree or equivalent qualification in an IT-related field, such as Computer Science, Information Technology, or Software Engineering.
  • Proven experience working with Sales Teams or in a Sales/pre-sales-facing role, demonstrating an understanding of the sales process and the ability to work collaboratively with sales professionals.
  • Data Engineering/Science/Generative AI Transition: A demonstrated track record of transitioning from software engineering to data engineering or data science.
  • Data Expertise: At least 2 years of experience in data-related roles, with a strong understanding of at least one of the following:
  • Data Engineering: Building and maintaining data pipelines, ETL/ELT processes, and working with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
  • Generative AI (GenAI): Experience with large language models (LLMs), prompt engineering, and building applications using GenAI technologies.
  • AI/ML: A solid understanding of Machine Learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

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