Structured around four core verticals—Accounting & Finance, Legal, Real Estate & Construction, and Technology & Data—it has carved out niche market authority.
Backed by the global Search Recruitment Group.
Regularly partners with high-profile law firms, real estate & construction firms, major corporates and tech/data teams — delivering mid‑ to executive‑level hires.
Engages in unusually personalized recruitment: leaders with decades of experience oversee deep-market and client immersion.
Operates from a flagship New York HQ, with growth across US and UK operations.
About the client
About the client
Information not given or found
Role
Description
platform security
monitoring
iac
kubernetes
python apis
mlops
Ensure platform security, compliance, and best-practice access controls.
Implement comprehensive monitoring, logging, and observability frameworks.
Lead DevOps and automation initiatives, including Infrastructure as Code (Terraform) and CI/CD workflows.
Develop clean, well-tested Python code for automation, infrastructure tooling, and services.
Architect and operate Kubernetes-based infrastructure (GKE) across a cloud environment.
Build and deploy high-performance Python APIs (FastAPI, Flask) powering ML predictions and application logic.
Collaborate cross-functionally and mentor junior team members.
Build and orchestrate scalable data ingestion and transformation pipelines using modern workflow tools (e.g., Dagster, Airflow).
Own the design and management of end-to-end MLOps pipelines supporting continuous training, deployment, monitoring, and versioning of ML models.
Implement automated testing and deployment pipelines (GitHub Actions).
Requirements
docker
kubernetes
python
airflow
gcp
mlops
**CANDIDATES MUST BE LOCAL TO NYC & OUR CLIENT CANNOT SPONSOR AT THIS TIME**Senior Data Engineer - Media & Digital Platforms
Deep understanding of Docker, Kubernetes, and infrastructure-as-code (Helm, Crossplane).
Hands-on experience with data orchestration tools (Dagster, Airflow).
Advanced proficiency in Python for development and automation.
Strong experience deploying APIs and backend services using FastAPI, Flask, or similar frameworks.
Expertise in SQL, schema design, and experience with both relational and NoSQL data stores.