About the role
Our company description
Mission is a platform for hiring, vetting, and managing software development talent. It enables our clients to connect with the world’s best talent to build mission-critical software products.
About the client
As a premier Google Cloud partner in data and analytics, our client delivers cutting-edge cloud data solutions to world-class organizations. By combining deep expertise in machine learning, data engineering, and analytics, they help businesses push the boundaries of modern technology.
Our client is a full-stack data consultancy with a clear mission — to become the market leader in Modern Data Stack consulting. Their portfolio spans from fast-growing North American scale-ups to well-established global tech companies, all benefiting from their advanced AI and data capabilities.
About the role
We are seeking a DevOps or Data Engineer with hands-on experience in cloud infrastructure, data migration, and containerized environments. The ideal candidate has previously worked on Azure-to-GCP migrations, understands both DevOps automation and data engineering pipelines, and can handle the transition of microservices and data systems with minimal downtime.
What You’ll Do
- Configure and manage Google Kubernetes Engine (GKE) clusters.
- Deploy and manage infrastructure using Terraform.
- Migrate FastAPI/Python microservices to GKE (including container image rebuilds).
- Implement automated scaling for streaming pipelines and services.
- Design and configure network topology including VPCs, subnets, and firewall rules for WebRTC traffic.
- Tune WebRTC stack architecture for GCP, including STUN/TURN server configuration.
- Plan and execute service mesh implementations.
- Manage GPU VM specifications and allocation strategies for compute-intensive workloads.
- Handle Azure to GCP microservice migration, ensuring performance and reliability.
- Configure Google Cloud Storage (GCS) and migrate existing Azure Blob Storage data.
- Execute Azure Event Hub → Google Pub/Sub migration for real-time data streaming.
- Build automated data migration pipelines from Azure Cosmos DB → PostgreSQL.
- Handle vector store data migrations, ensuring semantic search capabilities are preserved.
- Perform data validation and reconciliation to ensure successful end-to-end migration.
- Work with both Azure Cosmos DB and PostgreSQL, understanding schema mapping and data consistency.
Required Skills & Experience
- 5+ years of experience in DevOps or Data Engineering roles.
- Proven success in multi-cloud migrations (Azure → GCP).
- Strong experience with Terraform, GKE, Docker, and Kubernetes networking.
- Experience in Python, FastAPI, and modern data pipelines.
- Familiarity with vector databases and semantic search frameworks.
- Knowledge of service mesh architectures (e.g., Istio, Linkerd).
- Understanding of auto-scaling, load balancing, and GPU-based compute workloads.
This is as short term engagement until mid December with a chance to renew! Full overlap with EST timezone.
About the role
Our company description
Mission is a platform for hiring, vetting, and managing software development talent. It enables our clients to connect with the world’s best talent to build mission-critical software products.
About the client
As a premier Google Cloud partner in data and analytics, our client delivers cutting-edge cloud data solutions to world-class organizations. By combining deep expertise in machine learning, data engineering, and analytics, they help businesses push the boundaries of modern technology.
Our client is a full-stack data consultancy with a clear mission — to become the market leader in Modern Data Stack consulting. Their portfolio spans from fast-growing North American scale-ups to well-established global tech companies, all benefiting from their advanced AI and data capabilities.
About the role
We are seeking a DevOps or Data Engineer with hands-on experience in cloud infrastructure, data migration, and containerized environments. The ideal candidate has previously worked on Azure-to-GCP migrations, understands both DevOps automation and data engineering pipelines, and can handle the transition of microservices and data systems with minimal downtime.
What You’ll Do
- Configure and manage Google Kubernetes Engine (GKE) clusters.
- Deploy and manage infrastructure using Terraform.
- Migrate FastAPI/Python microservices to GKE (including container image rebuilds).
- Implement automated scaling for streaming pipelines and services.
- Design and configure network topology including VPCs, subnets, and firewall rules for WebRTC traffic.
- Tune WebRTC stack architecture for GCP, including STUN/TURN server configuration.
- Plan and execute service mesh implementations.
- Manage GPU VM specifications and allocation strategies for compute-intensive workloads.
- Handle Azure to GCP microservice migration, ensuring performance and reliability.
- Configure Google Cloud Storage (GCS) and migrate existing Azure Blob Storage data.
- Execute Azure Event Hub → Google Pub/Sub migration for real-time data streaming.
- Build automated data migration pipelines from Azure Cosmos DB → PostgreSQL.
- Handle vector store data migrations, ensuring semantic search capabilities are preserved.
- Perform data validation and reconciliation to ensure successful end-to-end migration.
- Work with both Azure Cosmos DB and PostgreSQL, understanding schema mapping and data consistency.
Required Skills & Experience
- 5+ years of experience in DevOps or Data Engineering roles.
- Proven success in multi-cloud migrations (Azure → GCP).
- Strong experience with Terraform, GKE, Docker, and Kubernetes networking.
- Experience in Python, FastAPI, and modern data pipelines.
- Familiarity with vector databases and semantic search frameworks.
- Knowledge of service mesh architectures (e.g., Istio, Linkerd).
- Understanding of auto-scaling, load balancing, and GPU-based compute workloads.
This is as short term engagement until mid December with a chance to renew! Full overlap with EST timezone.