851 to 875 of 3,811 GCP Jobs

turn inputs into actions, and uphold trust through integrity. Skills and Competencies Familiarity with cloud services and platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure Experience with source code management systems such as GitHub, Bitbucket, or GitLab Basic knowledge of Linux-based operating systems ...

HSMs), key management, service mesh security, and transport layer protocols across our cloud environments. Enterprise Architecture Delivery: Architect secure, scalable solutions across AWS and GCP, translating complex security requirements into simple, pragmatic design patterns for engineering teams. Secure Architecture Governance: Lead and assist with secure design reviews and threat modeling … Experience: Proven track record in a Information Security Architect or Senior Security Engineering role designing secure, distributed systems within modern cloud environments (AWS/GCP). Deep Cryptography Expertise: Comprehensive practical and theoretical knowledge of symmetric/asymmetric cryptography, PKI management, digital signatures, key management systems (KMS), and HSMs. Post ...

into solid technical solutions Identifying and resolving technical debt, and advocating for long-term maintainability Must-have: SQL Cloud experience - Azure preferred, AWS or GCP also considered Nice to have: CI/CD pipelines, Docker, or Kubernetes Microservices or event-driven architecture experience What We're Looking For Proven senior ...

matched by a pragmatic approach. Extensive Data Engineering Experience: A proven track record of building robust scalable data pipelines using modern cloud providers (Ideally GCP). Strong Programming Skills: Expert-level proficiency in Python, with a strong focus on building decoupled, testable functions and clear data contracts. Serverless & Event-Driven ...

platform engineering roles in a high-growth tech company (scale-up) or equivalent. Strong hands-on expertise with cloud platforms (AWS/Azure/GCP), infrastructure as code (ideally Terraform), containers (Docker), container orchestration (Kubernetes), and CI/CD tooling. Proven track record of building and managing CI/ ...

platform engineering roles in a high-growth tech company (scale-up) or equivalent. Strong hands-on expertise with cloud platforms (AWS/Azure/GCP), infrastructure as code (ideally Terraform), containers (Docker), container orchestration (Kubernetes), and CI/CD tooling. Proven track record of building and managing CI/ ...

using Auth0, alongside structured headless CMS architectures like Sanity. Monetisation, Analytics & Cloud Tooling: familiarity with Google Ad Manager, Stripe billing, HubSpot, Amplitude, and Google Cloud Platform services with Terraform. Bullish is proud to be an equal opportunity employer. We are fast evolving and striving towards being a globally-diverse community. ...

willingness to learn (or existing knowledge of) Spark. Proficiency with big data analytics technologies and public cloud platforms (AWS, Azure, or GCP). Hands‐on expertise in designing and delivering complex proofs‐of‐concept (PoCs). Pre‐Sales & Customer‐Facing Skills: Proven ability to engage with customers in a technical ...

both written and verbal Public Cloud Architecting: Hands-on experience designing and implementing big data architectures within major public cloud environments (AWS, Azure, or GCP) Strategic Enablement & Community Mentorship Experience collaborating with Professional Services and Global Systems Integrators to standardize migration delivery methodologies and ensure smooth handoffs. About Databricks Databricks ...

back end Experience building microservices on container based infrastructure (Kubernetes, Docker, etc.) Solid hands-on experience with a major cloud platform (AWS, Azure, or GCP) Strong grounding in Agile/Lean ways of working The Work We work across a range of well-known tech organisations and brands, with ongoing ...

Expertise in Elasticsearch management, indexing, and query optimisation. Knowledge of data modelling, warehousing, and modern data platform architectures. Familiarity with cloud platforms (AWS, Azure, GCP) in secure environments. Understanding of data security, governance, and information assurance. Experience with DevOps practices, CI/CD, and Infrastructure as Code. Desirable: Experience within ...

industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning ...

within multidisciplinary teamsExperience Required:·Experience designing AI, ML or modern data architectures within enterprise environments·Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies·Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments·Experience with LLMs, prompt engineering, embeddings, semantic ...

within multidisciplinary teamsExperience Required:·Experience designing AI, ML or modern data architectures within enterprise environments·Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies·Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments·Experience with LLMs, prompt engineering, embeddings, semantic ...

clustering, and correlation algorithms. Generative AI: Experience with LLM prompting, Retrieval-Augmented Generation (RAG), and LangChain. Cloud Infrastructure: Deep understanding of AWS, Azure, or GCP infrastructure componentsAdditional Preferred Qualifications: Experience with enterprise observability and AIOps platforms such as ServiceNow ITOM, Splunk, Dynatrace, Datadog, BigPanda, New Relic, or similar platforms. Familiarity ...

industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production‐grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine‐tuning ...

strong coaching and mentorship style Deep understanding of modern data architectures, data integration best practices, orchestration patterns, and cloud-based data platforms (AWS, GCP, or Azure) Technical credibility with data engineering practices: strong grasp of SQL, data modeling, pipeline design, and tools like dbt, Airflow, Fivetran, and similar Hands ...

delivery experience with contribution to practice growth through proposition development and knowledge sharingCloud-native architecture expertise - Hands-on experience with AWS/Azure/GCP, data lakes, real-time streaming, and infrastructure-as-code Experience & Qualifications: Experience: Minimum 7–10 years in data architecture, engineering, or consulting roles, with ...

operating production services at scale. Hands-on experience building backend platforms, developer tools, or infrastructure products. Familiarity with cloud platforms such as AWS, GCP, or Azure and container technologies including Docker and Kubernetes. Proven ability to take ownership of large technical initiatives from architecture through production. Commitment to software quality ...

industry DS/ML experience, with a focus on either: ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance. Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning ...

8+ years of commercial software engineering experience. Experience owning and operating production distributed systems end-to-end. Strong TypeScript or Python expertise. Deep Google Cloud Platform experience, or equivalent cloud platform knowledge. Proven track record of designing, building and operating large-scale systems. Improving engineering standards, quality processes or software ...

patterns, DRY principles, Clean Code, and microservices architecture.* Technical Ecosystem: Proficient with modern DevOps and cloud tools, including Git, Docker, Kubernetes, and cloud platforms (GCP preferred).* Financial Domain Awareness: Good foundational understanding of financial products, risk management concepts, or risk methodologies (e.g., SPAN, VaR).* Analytical Aptitude: Strong mathematical ...

them to solve specific problems. Solid engineering skills, including designing and implementing services/data models and features. Expertise with cloud computing platforms (AWS, GCP, or Azure) and containerisation tools (e.g., Docker, Kubernetes). Expertise with modern data platforms (e.g., BigQuery/Databricks) and data processing workflows (ETL, pipelines). ...

engineering fundamentals: cloud, reliability, security, monitoring, CI/CD Technical environment (Not hands-on coding daily, but technically credible) Cloud: AWS/Azure/GCP AI/ML delivery: model deployment, MLOps/LLMOps, monitoring, iteration Platform foundations: Kubernetes (EKS/AKS), CI/CD, GitOps concepts Observability: metrics, logs ...

Strong hands-on experience with: GKE (Google Kubernetes Engine) Cloud Run Cloud Functions Pub/Sub Cloud SQL VPC Networking IAM Cloud Monitoring Secret Manager Cloud Storage Infrastructure as Code (IaC) Expert-level knowledge of ...