Data Specialist/Engineer

Descrição do trabalho

Fundraisr is seeking a Lisbon-based Data Engineer to architect the core intelligence of the largest AI raise in Portugal's history. In this role, you will be responsible for scaling a proprietary database of over 1.5 million investors, transitioning our data layer from basic filtering to a sophisticated, AI-driven matching engine. You will implement advanced semantic search capabilities using text-embedding-3-small model and vector databases like Pinecone or pgvector to identify thematic alignment between startups and investors.

Your work will directly solve the systemic inefficiencies of traditional fundraising by replacing manual, network-gated models with an automated, merit-based system built on PostgreSQL and JSONB.Key responsibilities include developing a weighted composite scoring algorithm that balances semantic similarity, rule-based compliance, and real-time engagement signals to prioritise outreach.

You will design and manage automated data pipelines to extract critical financial metrics and investment theses from pitch decks and unstructured web data. Additionally, you will oversee the technical migration to Python-based micro-services for compute-intensive tasks such as predictive deal scoring and investor research summarisation.

By building high-performance, RLS-protected data environments, you will ensure that Fundraisr remains the institutional-grade SaaS alternative for the next generation of global capital allocators

Role Description

This is a full-time, on-site role based in Lisbon for a Data Specialist/Engineer. The professional in this role will be responsible for developing and maintaining robust data engineering pipelines, implementing data modeling solutions, managing Extract, Transform, Load (ETL) processes, and designing data warehousing solutions. The individual will also conduct in-depth data analytics to support business decisions and ensure the integrity and efficiency of Fundraisr’s data systems.

• Qualifications
• Proficiency in Data Engineering and expertise in Data Modeling techniques
• Experience with Extract Transform Load (ETL) processes and Data Warehousing systems
• Strong skills in Data Analytics for extracting meaningful insights to support business decisions
• Knowledge of database architecture, structured query languages (SQL), and data visualization tools
• Strong problem-solving skills and attention to detail
• Relevant degree in Computer Science, Information Systems, Data Science, or a related field
• Experience in the financial technology industry is a plus but not required