We're an ambitious, talented & international team of + eager to build high-quality solutions with real impact on the economy & society.
Backed by strong investors & strategic partners across the fintech sector, we build a suite of
using cutting-edge technology: AWS cloud-first architecture, Glue + Pyspark orchestration for Big Data, multi-agent AI systems on Amazon Bedrock, AI-accelerated development with
, modern stack (Spring Boot, React-Redux) for app environment.
The real challenge is execution: delivering fast without compromising quality. This squad monitors external signals — from minimum wage changes and commodity prices to M&A; activity and regulatory shifts — and cross-references them automatically with our proprietary microsector intelligence to produce company-level impact assessments across multiple markets.
on AWS (Glue, Step Functions, Lambda, S3, Athena, EventBridge) to capture, normalise, and enrich quantitative and qualitative external signals in near real-time
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, mentoring them on architecture decisions, data quality practices, best practices across the squad:



testing, validation, orchestration, observability, CI/CD, documentation and the integration of analytical models into production
that link external signals (SMI, energy prices, interest rates, raw materials) to company-level exposure using mscope's 550+ microsector taxonomy and financial data
: SFTP/S3 data feeds, API services, and the native integration module within our Intelligence front-end
of experience in data-intensive roles (Data Engineering, Analytics, or Data Science), with at least
for data workloads (S3, Glue, Lambda, Step Functions, Athena, RDS, EventBridge)
for data engineering and analytical applications;
proficiency for complex querying and data modelling
integrating heterogeneous external data sources (APIs, web scraping, structured feeds) at scale
Hands-on experience with event-driven architectures and real-time data processing (, …)
PySpark, Glue) and distributed data proc

📌 Technical Service Team lead (España)
🏢 mscope
📍 España