Deloitte
Cloud Engineer, Forensic & Financial Crime Technology Advisory and Data Analytics
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Designing, building and running secure, production-grade cloud platforms that our clients can trust with their most sensitive data, it’s just another day at the office for our Financial Crime Technology Advisory and Data Analytics experts.
This is your opportunity to join Deloitte's Financial Crime Technology Advisory and Data Analytics team. Our rapidly growing practice is expanding to meet large and consistent client demand for cloud, data and AI-enabled solutions. The team comprises a group of specialists drawn from a wide range of different professional and technical backgrounds. We apply our combined skills and experience to find new ways of solving our clients’ most complex technology, data, and analysis challenges.
Working with the world’s largest and most complex financial organisations, you will own the architecture, deployment and operation of cloud platforms and data/AI workloads at scale. You will make the design decisions that balance security, resilience, performance and cost, and you will be accountable for how those decisions hold up in production. Collaborating with colleagues and industry leaders, you will have an opportunity to grow your industry presence and be recognised as a leader in your domain.
No two projects are the same, however the majority will involve architecting and operating cloud, data and web solutions in highly regulated environments. Typical projects include defining target-state cloud architectures and landing zones, delivering solutions directly on the client’s cloud estate, building data and AI pipelines, and hardening, migrating or optimising existing workloads for security, resilience and cost. Most of the projects will be in the regulated financial services sector.
Away from project work, we offer both formal and informal support for continuous professional development, to accelerate your career progression within a rapidly growing team.
We encourage consideration of flexible ways of working, both formal and informal arrangements that allow for the best outcomes for our people and our clients. If this opportunity is of interest to you with some flexibility, please do discuss with us.
Connect to your career at Deloitte
Deloitte drives progress. Using our vast range of expertise, we help our clients’ become leaders wherever they choose to compete. To do this, we invest in outstanding people. We build teams of future thinkers, with diverse talents and backgrounds, and empower them all to reach for and achieve more.
What brings us all together at Deloitte? It’s how we approach the thousands of decisions we make every day. How we behave, our beliefs and our attitudes. In other words: our values. Whatever we do, wherever we are in the world, we lead the way, serve with integrity, take care of each other, foster inclusion, and collaborate for measurable impact. These five shared values lead every decision we make and action we take, guiding us to deliver impact how and where it matters most.
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Using cutting edge technology, you’ll work alongside colleagues, often in multi-disciplinary teams, helping to solve our clients’ most significant challenges. As a senior member of the team you will lead the technical design and hands-on delivery of cloud solutions, frequently working directly within the client’s own cloud environment, controls and change processes.
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You will be expected to go deep as well as broad: making and defending architecture decisions, writing and reviewing infrastructure-as-code and application code, and owning solutions through to production operation. Specific responsibilities will include:
- Owning end-to-end solution and platform architecture across compute, storage, data, networking and identity: producing target-state designs, reference architectures, well-architected reviews and trade-off analysis, and documenting decisions as ADRs;
- Designing and implementing secure landing zones and multi-account / multi-subscription topologies, including hub-and-spoke networking, private connectivity (private endpoints / PrivateLink / Private Service Connect), DNS, and network segmentation;
- Building and operating workloads as Infrastructure as Code (Terraform, Bicep/ARM or CloudFormation) with modular, reusable components, policy-as-code guardrails and automated drift detection;
- Designing and deploying containerised and serverless workloads: Kubernetes (AKS/EKS/GKE), serverless functions and managed app platforms, including autoscaling, ingress, service mesh and zero-downtime deployment strategies (blue/green, canary);
- Building CI/CD pipelines and GitOps workflows (GitHub Actions, Azure DevOps, Argo CD/Flux) with automated testing, security scanning (SAST/DAST, IaC and container scanning) and supply-chain controls;
- Architecting data and AI platforms (data lakes/lakehouses, warehouses, streaming and event-driven patterns) and integrating managed AI/model services (Azure OpenAI / AI Foundry, AWS Bedrock, GCP Vertex AI), including retrieval-augmented generation, vector search and secure prompt/data handling;
- Engineering for reliability and observability: defining SLOs/SLIs, instrumenting metrics, logs and traces (OpenTelemetry, Azure Monitor, CloudWatch, Prometheus/Grafana), and leading incident response, DR and resilience testing;
- Embedding security and compliance by design: IAM least privilege, secrets and key management (Key Vault/KMS/Secret Manager), encryption in transit and at rest (including CMK/BYOK), private endpoints, network policy, data residency and data-zone requirements, and UK/EU GDPR and financial-services regulatory obligations;
- Owning FinOps and cost optimisation: right-sizing, commitment-based discounts, tagging/showback and architectural changes that materially reduce run cost;
- Providing hands-on technical leadership and SME input: setting engineering standards, reviewing code and designs, mentoring engineers, and managing technical risk and quality across the workstream; and
- Evaluating and prototyping new cloud and AI services, and contributing to the team’s reusable assets, accelerators and reference implementations.
Connect to your skills and professional experience
Essentials:
- Proven experience designing and operating production cloud solutions, with deep hands-on expertise in at least one of Azure, AWS or GCP and the ability to both build and run/maintain what you deploy;
- Strong architecture fundamentals across compute, storage, databases, networking and identity, and a track record of making and defending design trade-offs in regulated environments;
- Expert-level Infrastructure as Code (Terraform and/or Bicep/ARM or CloudFormation) and automation, building modular, reusable, tested infrastructure rather than click-ops;
- Hands-on experience with containers and orchestration (Docker + Kubernetes: AKS/EKS/GKE) and with serverless and managed application platforms;
- Solid software engineering skills. Comfortable coding and reviewing in at least one of Python, C#, TypeScript/Node.js or Java, and building/consuming REST/gRPC APIs;
- Practical experience of CI/CD and DevOps/GitOps, including automated testing and security scanning in the pipeline;
- A strong, demonstrable security posture, IAM/least privilege, key and secrets management, encryption (incl. CMK/BYOK), private networking, and awareness of data residency (e.g. Azure data zones) and UK/EU GDPR obligations;
- Experience integrating managed AI/model services and building data pipelines to support them;
- Ability to lead a workstream and mentor engineers, set technical standards, and communicate complex designs clearly to both technical and non-technical (including senior client) audiences.
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Desirables:
- Azure: Blob/ADLS Gen2, Functions, App Service, SQL Database, Cosmos DB, AKS, API Management, Entra ID, Azure OpenAI, Azure AI Search, AI Foundry, Key Vault, Private Link, Azure Monitor/Log Analytics, Azure Policy, Bicep;
- AWS: S3, Lambda, VPC, RDS/Aurora, DynamoDB, ECS/Fargate, EKS, API Gateway, IAM, Bedrock, KMS, PrivateLink, CloudWatch, CloudFormation/CDK;
- GCP: Cloud Storage, Cloud Run, BigQuery, GKE, Vertex AI, Cloud IAM, VPC Service Controls, Cloud Monitoring/Logging;
- Data & AI: data lake/lakehouse and warehouse patterns (e.g. Databricks, Snowflake, Synapse/Fabric, BigQuery), streaming/event-driven architectures (Kafka/Event Hubs/Pub/Sub), and LLM/RAG patterns with vector databases;
- Observability & reliability: OpenTelemetry, Prometheus/Grafana, ELK, distributed tracing, SRE practices, chaos/DR testing;
- Security & governance: Zero Trust, CIS benchmarks, policy-as-code (OPA/Sentinel/Azure Policy), SIEM integration, and cloud security posture management (CSPM);
- Relevant certifications, e.g. Azure Solutions Architect Expert / DevOps Engineer Expert, AWS Solutions Architect Professional, Google Professional Cloud Architect, or CKA/CKAD;
- Experience of working on projects for external clients; and
- Experience of working in or on projects in regulated industries, particularly financial services.
Connect to your business - Strategy, Risk & Transactions Advisory
In an ever-evolving world, there are no certainties in business. Our teams help clients to navigate risks, process major transactions and deliver transformational change that will future-proof their business. Join us to make a positive difference.
Forensic & Financial Crime
Our teams in Forensic and Financial Crime provide proactive advice, transformation and operational support to help clients protect their brand and navigate financial crime risks, including money laundering, fraud and corruption.
Personal independence
Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (e.g., in relation to any financial interests
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