Abou SANOU
Quantitative Data Engineer & Quant Developer
Intro
What I am all about.
I am Abou Sanou, a quantitative data engineer and quant developer currently leading data initiatives.
Objective
I build quantitative data ecosystems that help hedge funds and trading desks discover signals, validate strategies, and operationalize execution. I am focused on teams where I can combine quantitative development, distributed data engineering, and risk modeling to accelerate research and production deployment.
Expertise
Core domains across quantitative research enablement, market data, and platform
reliability.
01
Market Data Engineering
Building resilient Spark/Airflow/Databricks pipelines that normalize tick data, alternative datasets, and valuations while preserving lineage.
02
Cloud & Low-Latency Infrastructure
Designing secure AWS estates for streaming, serverless research services, and IaC-managed analytics clusters tuned for quant workloads.
03
Risk & Valuation Analytics
Delivering pricing engines, factor models, and risk dashboards that combine deterministic analytics with ML-driven insights.
04
Observability & Controls
Implementing Datadog-first telemetry, anomaly detection, and governance to keep model outputs auditable and production data compliant.
05
Resource Optimization
Driving cloud and compute efficiency (Spark, Glue, MWAA) to reinvest budget into research scale—achieved 90% FinOps savings for analytics estates.
06
Quant Platform Leadership
Translating research requirements into engineering backlogs and mentoring data, quant, and reliability teams on shared standards.
Skills
Platforms and technologies I rely on to deliver data products at scale.
Technical Skills by Language & Domain
Snapshot of the tools I apply most in quantitative finance environments.
Languages
- Python (core quant stack: Pandas, NumPy, PySpark, FastAPI)
- C++ (pricing utilities, low-latency services)
- Java (Spring Boot data services)
- R & SQL for statistical analysis and reporting
Quant Domains
- Market data & microstructure
- Portfolio analytics, performance, attribution
- Risk, valuation, collateral & treasury data
- Investor relations and regulatory reporting data marts
Platforms & Tooling
- Apache Spark, Databricks, Airflow, Kafka
- AWS Glue, Lambda, Step Functions, MWAA, S3
- Terraform, Jenkins, GitLab CI, Datadog
- ML/RL frameworks: PyTorch, TensorFlow, RLlib, scikit-learn
Target Roles & Career Focus
Where I want to create outsized impact next.
I am pursuing roles that sit between quantitative research and engineering inside hedge funds, proprietary trading firms, and multi-strategy platforms.
- Quantitative Data Engineer / Lead – owning data acquisition, research platforms, and model delivery.
- Quant Developer – partnering with PMs and researchers on pricing, execution, and risk tooling.
- Market Microstructure & Platform Engineer – optimizing ingestion, feature stores, and observability for systematic desks.
I gravitate toward systematic macro, digital assets, multi-strategy, and crossover funds where data agility and governance are equally valued.
Experience
Quant-ready data and analytics programs spanning investment banking, private markets,
and mission-critical platforms.
2023 - Present
Bpifrance
Tech Lead Data
France
Lead three teams across the investment value chain—Data Processing, Reporting, and Financial Performance—representing ~20 data engineers, analysts, and financial experts servicing quant and risk stakeholders.
Designed a new AWS-based datalake (S3, Glue, Athena, MWAA, Lambda) with HSM-backed encryption and Terraform IaC to host portfolio, market, and investor datasets.
Built CI/CD foundations with Jenkins and a Spark-based framework that standardizes every data preparation pipeline for research, backtesting, and regulatory packs.
Migrated Matillion workloads to AWS Glue, cutting incidents by 90%, keeping indicator availability at 99.9%, and reducing FinOps costs from EUR 30k to EUR 2k.
Implemented Datadog-driven monitoring, alerting, and APM plus data modeling standards for market data, risk, legal reporting, and portfolio-management products.
2021 - 2023
Bpifrance
Data Engineer
France
Developed large-scale preparation pipelines in Python and Airflow for company performance tracking, valuations, transactions, funds, conflicts of interest, and fund-of-funds data used by front-office and risk analysts.
Processed hundreds of gigabytes of transaction data per day while ensuring data quality and timely delivery to downstream risk and reporting teams powering scenario analysis and backtesting.
2018 - 2019
CHU Sourou Sanou
Ingénieur Data/Logiciel
Burkina Faso
Implemented a diabetes patient management platform deployed on AWS with Amazon Redshift, including a dedicated data warehouse that follows an OLAP approach.
Delivered patient document features, FHIR-compliant data structures, and RBAC-secured access for clinicians and researchers.
2017 - 2018
Centre de Recherche en Santé de Muraz
Ingénieur Logiciel
Burkina Faso
Developed a Java Spring Boot project management tool for one of West Africa's largest health research institutions to track finances, team objectives, and organization-wide KPIs.
Technical Stack
- Core Skills: Data Engineering, Software Architecture, Market Data Systems, Cloud Infrastructure
- Programming: Python, C++, Java, R
- Tools: Apache Spark, Databricks, AWS (Glue, Lambda, S3, Step Functions), Airflow, Kafka
- Concepts: CI/CD, Data Modeling, Deep Learning, Observability, FinOps Optimization
Community Engagements
- Board Member – NGO UAEFI
- Co-creator – Struct'IOT Association promoting IoT adoption
- Panelist – ITAUN, Tunisia
- Permanent Member – FEED, France-Burkina
- Volunteer Lecturer – Virtual University of Burkina Faso (ML/DL)
- Volunteer – Rotaract Club, Burkina Faso
Publications
Towards a plant pathologies detection solution (2022) Read on ResearchGate
Education
2025 - 2026
ESSEC Business School & CNAM
Master 2 Financial Markets and Asset Management
France
Specialization in financial mathematics, derivatives pricing, risk modeling (VaR, ES), stochastic calculus (Black-Scholes, Greeks), portfolio theory, machine learning, and blockchain.
2023 - 2024
CNAM
Master 1 Finance (Mention Très Bien)
France
Focus on financial analysis, derivatives pricing, fixed income, risk management, and quantitative finance.
2020 - 2021
Université Jean Monnet
MSc Computer Science, Data and Connected Systems (Mention Très Bien)
France
2019 - 2020
Université Marie et Louis Pasteur
Master Embedded Systems and IoT (Mention Bien)
France
2018 - 2019
Université Polytechnique de Bobo-Dioulasso
Master 1 Decision Support Systems
Burkina Faso
2015 - 2018
Université Polytechnique de Bobo-Dioulasso
Bachelor Information Systems (Mention Très Bien)
Burkina Faso
Profiles
Where I publish open-source work, articles, and research.
Projects & Impact
Selected initiatives that illustrate how I blend data, AI, and operations.
Bpifrance Datalake Modernization
Delivered a fully encrypted AWS datalake (S3, Glue, Athena, MWAA, Lambda) with Terraform-driven IaC to support investment reporting and risk analysis.
AWS Glue Migration Accelerator
Migrated legacy Matillion workloads to AWS Glue and Spark, reducing incidents by 90%, sustaining 99.9% availability, and shrinking FinOps costs from EUR 30k to EUR 2k.
Diabetes Patient Management System
Built a PHP + AWS Redshift platform for Sourou Sanou University Hospital to manage patient records, FHIR-compliant data, and RBAC-secured analytics.
Portfolio
Here it gets interesting.