Senior Engineering Manager - Supply & Demand

Team: Engineering Commodities

Location: London, Paris

Commitment: Full-time

Workplace Type: hybrid

Your mission is to:

• Build and sustain an autonomous crew that owns systems end-to-end, from data pipelines to APIs including production operations, incident management, and on-call, while removing organisational blockers to maximise delivery focus.

• Champion SLO-driven reliability (via Datadog), with robust runbooks, blameless post-mortems, and a strong emphasis on proactive observability to detect issues before users.

• Structure and prioritise work with clear milestones and a consistent delivery cadence, balancing short-term operational needs with longer-term strategic initiatives; use metrics (e.g. velocity, cycle time, effort allocation) to inform decisions and ensure transparency.

• Maintain high engineering standards by creating space for testing, automation, observability, documentation, and technical debt reduction; guide architectural decisions across Python and TypeScript systems.

• Oversee AWS infrastructure (Terraform-managed) and platform components (ArgoCD, Airflow), ensuring scalability, reliability, and cost efficiency while supporting expansion into new commodity domains.

• Develop and retain engineers through clear goals, regular feedback, and career development, fostering high performance while addressing challenges with empathy and clarity.

• Partner with recruitment to maintain a strong hiring bar and ensure the team is appropriately staffed and balanced in skills and seniority.

• Collaborate closely with Product, Research, and Data teams, communicating progress, managing risks, and increasing the visibility and impact of the crew’s work.

• Leverage retrospectives, health checks, and existing metrics to drive continuous improvement, building on an already strong data-driven culture.

• Share and scale best practices across the wider engineering organisation, contributing to broader technical excellence and consistency.

 

 

 

Skills & Experience

Experience & Leadership

• Overall 8+ years of engineering management experience, including at least 3 years leading teams of 5+ engineers on production, data-intensive systems.

• Proven success building autonomous, high-performing teams that own systems end-to-end—from data ingestion to client-facing APIs.

• Experience managing distributed or remote teams across multiple time zones.

• Track record of recruiting, developing, and retaining engineering talent, with confidence in performance management and career growth conversations.

Technical & Operational Expertise

• Strong experience managing teams that build and operate scalable data pipelines or ETL systems using tools like Airflow, Dagster, or Prefect.

• Hands-on background with Python backend systems (FastAPI, pandas/polars, SQLAlchemy), as IC or manager.

• Proficient with cloud-native infrastructure on AWS (or equivalent), including RDS/Aurora PostgreSQL, S3, Kubernetes/ECS, IAM, and Terraform.

• Familiarity with CI/CD pipelines, GitOps practices, and deployment automation (GitHub Actions, ArgoCD).

• Strong operational mindset: SLOs/SLIs, incident management, on-call rotations, and post-mortems.

Nice to have

Experience managing teams building APIs in TypeScript/Node.js (NestJS, Express, GraphQL/Apollo); the crew’s API layer is TypeScript-based.

Familiarity with production ML systems (e.g., Prophet-based anomaly detection for data quality).

Experience in commodities, energy, or fintech domains.

Exposure to Dataiku or similar data science platforms used by analyst teams.

Experience with monorepo architectures and shared library/framework design patterns.

Familiarity with observability tooling (Datadog, Prometheus, Grafana) and API gateway management (Kong).

Experience managing teams serving both internal platform consumers and external API clients (dual-interface API patterns).

Background in organisations using tribe/squad/crew models (Spotify model or similar).