Abaka AI is committed to being the world's most trusted data partner for AI companies, supporting over 1,000 industry leaders. The Data Acquisition Engineer will own and scale the raw data supply ecosystem, focusing on creating scalable infrastructure for managing data suppliers globally while designing automation and internal tools.
Responsibilities:
- Build automated pipelines and AI-driven workflows to discover and evaluate new raw data sources
- Design and implement internal tooling for supplier tracking, scoring, and performance management
- Experiment with scraping, APIs, enrichment tools, and automation platforms to increase sourcing efficiency
- Aggressively identify and outreach to new data suppliers across global markets
- Evaluate supplier quality, reliability, and scalability in partnership with internal teams
- Manage ongoing vendor relationships, ensuring quality, cost, and delivery standards are met
- Track supplier performance using quantitative metrics and continuously improve processes
- Collaborate cross-functionally with Data Engineering, Research, Product, GTM, Legal, and Finance to align supply with business needs
- Support commercial discussions and contract processes with guidance from leadership
- Build scalable systems that increase data throughput without increasing headcount
Requirements:
- Strong technical foundation (engineering, data, scripting, automation, or systems building)
- Experience building projects, tools, or pipelines from 0→1
- Comfortable using AI-native tools (e.g., LLM agents, Cursor, automation platforms, workflow builders)
- High ownership mindset with the ability to operate independently in ambiguous environments
- Strong written and verbal communication skills
- Interest in AI, machine learning, and data infrastructure
- Growth-oriented mindset with bias toward experimentation and rapid iteration
- Experience in startup or high-growth environments
- Exposure to data pipelines, scraping, APIs, or automation workflows is a strong plus
- Prior vendor management experience is not required