Senior Data Engineer, Descartes & Mauss
Feb/Mar 2026
2+ days a week in office
AI-powered growth consulting
Be an early applicant
AI-powered growth consulting
21-100 employees
Be an early applicant
2+ days a week in office
21-100 employees
Company mission
To build critical paths for companies to find growth and resilience.
Role
Who you are
- MANDATORY: 4–6 years of experience as a Data Engineer or Backend/Data hybrid
- Strong Python & SQL skills, with experience building production-grade pipelines
- Hands-on experience with large-scale data processing (Spark) and lakehouse technologies (Delta Lake)
- Proven ability to productionise ML/GenAI pipelines and integrate them into backend systems
- Familiarity with cloud infrastructure (AWS preferred)
- Good communication skills and a collaborative mindset
- Ability to take ownership, make sound technical decisions, and maintain high engineering standards
- If you’re excited about this role but don’t meet every single requirement, we still encourage you to apply
What the job involves
- We’re looking for a mid–senior Data Engineer (4–6 years of experience) who can take ownership across data architecture, ML/GenAI pipeline PoC-to-Production, and backend integrations
- You’ll play a key role in turning experimental models into reliable product features, shaping the data platform, and raising engineering quality across the team
- You’ll report to the Engineering Manager and collaborate closely with our Data Science team, supporting them in taking research-grade pipelines into a production-ready environment
- This is a great fit for someone who enjoys both building and improving systems end-to-end: data, backend, infrastructure, and everything in between
- 1) ML & GenAI Production
- Convert experimental DS/ML/GenAI workflows into scalable, reliable production pipelines
- Integrate OpenAI, AWS Bedrock, and internal models into product-critical processes
- Work with Data Scientists to design model-serving strategies and orchestration flows
- Deploy and monitor multi-stage workflows leveraging AWS (Lambda, Batch, Glue, ECS)
- 2) Backend & API Integration
- Build and maintain data-driven features using FastAPI and Django
- Partner with product teams to expose new data capabilities through clean, well-structured APIs
- Help define and enforce backend/data patterns, code style, and technical quality standards
- 3) Data Pipelines & Platform
- Improve and extend ingestion pipelines using PySpark, Delta Lake, and AWS
- Work with structured, semi-structured, and unstructured datasets at scale
- Maintain Delta tables, audit systems, and metadata layers
- Support the evolution of our data models, lakehouse architecture, and storage strategies
- 4) Engineering Quality & Ownership
- Participate in code reviews, drive best practices, and improve the engineering culture
- Contribute to architectural discussions and technical decision-making
- Help shape internal standards for data validation, reliability, and observability (logs, metrics)
- 5) Tech Stack You’ll Use
- You don’t need to know everything on day one — but experience with most of these is expected:
- Python, SQL
- FastAPI, Django
- PySpark, Delta Lake
- PostgreSQL, DynamoDB
- AWS: Lambda, Batch, Glue, EC2, ECS, S3
- OpenAI / AWS Bedrock APIs
- Haystack (search/LLM pipelines)
- Docker, GitHub Actions
- Bonus: event-driven architectures, Terraform, CI/CD, observability tooling
Application process
- Starting date: January 31, 2026
- 30 min chat with HR team for a culture-fit introduction call
- 30 min chat with the hiring manager (Harsha, Engineering Manager)
- Case study
- Office tour & team meeting (if Paris-based)
Our take
Descartes & Mauss is emerging into the field of "StraTech," which leverages AI to revolutionise strategy-making. It's approach combines data modelling with social science methodologies, allowing businesses to simulate potential futures and make more informed decisions.
By creating digital twins of companies and their markets, Descartes & Mauss helps its users to optimise strategy and planning. Its market analysis processes millions of data signals across various dimensions such as technology, competition, and politics. Plus, it guides companies from insight to action, utilising generative AI to create actionable plans.
Already, Descartes & Mauss has secured significant funding that will help accelerate product development and expand its sales teams. Looking ahead, the company aims to establish itself as a global leader in the StraTech sector, continuing to innovate and refine its AI-driven solutions to empower companies in an increasingly unpredictable world.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Jun 2024
$6.5m
SEED
Total funding: $6.5m
Company benefits
- Hybrid working: 2 days a week in the office
- WeWork office access worldwide
- Swile Card
- 50% of the public transport cost is reimbursed
- Extra Insurance with Mutuelle
- Birthday off policy
- Employee wellbeing initiatives
Company HQ
Saint-Lambert, Paris, France
Leadership
Maurice NDiaye
(Co-Founder & CEO)Prior work includes being a Partner at Synomia and a Teacher in Data Marketing for Sciences Po.
Yannis Kavounis
(Co-Founder & CCO)Previously spent over 15 years at Kantar in various roles, including Senior Director of Brand & Marketing Consulting.
Thomas Decerisy
(Co-Founder & COO)Previously spent nearly 5 years at iziwork as a Director of Marketplace and VP of Sales & Marketing Prior to that, they worked at Salesforce in Buiness Development roles and McKinsey & Company as an Associate and Engagement Manager.
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