The Cloud Data Architect will design, build, and operationalise modern cloud data platforms and integration solutions for nxzen’s critical national infrastructure clients (primarily energy and utilities such as water, gas, and electricity, expanding in the mid-term to rail and highways sectors) in the UK, Australia, and internationally. The role sits at the heart of two of the five pillars of nxzen’s Data & AI practice: Data Platforms & Architecture and Data Engineering & Integration. Based in nxzen’s
Global Capability Centre in Hyderabad or Bangalore, you will report to the Director of AI and Analytics, working as part of nxzen's Data & AI practice leadership. This is a hands-on technical leadership role: you will design reference architectures, configure cloud landing zones, build integration patterns, write and supervise production code where appropriate, and lead teams delivering production-grade data platforms for critical national infrastructure operators.
The role spans the full data platform lifecycle: from target architecture definition and platform selection, through landing zone design, ingestion and integration build, transformation and curation, to operational handover and ongoing optimisation. Your core discipline is cloud data architecture and data engineering across at least two hyperscalers (Azure, AWS, or GCP), combined with a strong grasp of modern data architecture patterns (data lakehouse with medallion layering, data mesh, data fabric, data products). You will work across IT, OT, ET and ERP source systems, sing nxzen's utility canonical data model (IEC CIM-aligned) and reference data models as the integration backbone. You will collaborate closely with data governance, analytics, and data science leads to ensure platforms are AI-ready, governable, and regulator-defensible.
You will contribute to nxzen’s IP and solution development, and support pre-sales by producing reference architectures, target operating models, build-vs-buy assessments, proof-of-value prototypes, and contributing to proposals and commercial presentations under the direction of the Director of AI and Analytics and the UK Head of Data & AI. Success in this role requires deep cloud and data engineering credibility, the ability to translate client business outcomes into pragmatic platform designs, comfort operating in regulated environments, and a genuine interest in energy and infrastructure as an application domain.
Key responsibilities
The Cloud Data Architect will design and deliver cloud data platform and integration solutions across nxzen’s critical national infrastructure client portfolio, combining architectural depth with hands-on engineering delivery. You will work on client engagements from discovery through to production, collaborating with onshore/offshore consultants, data engineers, data governance specialists, data scientists, and client technical teams.
You will own end-to-end platform design and build, from target architecture and landing zone through to ingestion, transformation, integration, and operational handover, ensuring solutions are production-grade, secure, cost-efficient, and aligned to client requirements and nxzen’s delivery standards.
A key focus will be translating client business and regulatory outcomes into pragmatic, scalable platform designs that deliver measurable value for regulated critical national infrastructure clients. You will contribute to the growth and technical maturity of nxzen’s Global Capability Centre data platform and engineering function.
· Design and deliver target-state cloud data platforms across hyperscalers (Azure, AWS, GCP) and platform technologies (Microsoft Fabric, Databricks, Snowflake), applying
modern architecture patterns including data lakehouse (with medallion layering), data mesh, data fabric, and data products, selecting the right pattern for the client’s maturity and scale.
· Design and configure secure, governed cloud landing zones, including networking, identity, key management, cost management, observability, and policy-as-code, aligned to hyperscaler Well-Architected Frameworks (Azure Well-Architected Framework, AWS Well-Architected, Google Cloud Architecture Framework) and to UK utilities regulatory expectations.
· Architect and build data engineering pipelines for analytics, data product and AI/ML workloads (batch, streaming, change data capture) using PySpark/Spark, SQL, dbt, Delta Lake, and hyperscaler-native services (Azure Data Factory, Synapse, Microsoft Fabric Data Factory, AWS Glue, EMR, Step Functions, GCP Dataflow, Dataform, BigQuery), with orchestration through Airflow, ADF, or equivalent.
· Architect and deliver enterprise application and system integration solutions across IT, OT, ET and ERP systems using nxzen's tooling stack (Informatica, MuleSoft, IBM ACE, WebMethods), applying API-led, event-driven, and message-based patterns, with secure IT/OT boundary controls (IDMZ, data diodes, OPC UA gateways, MQTT/Sparkplug B Unified Namespace where appropriate).
· Apply nxzen's utility canonical data model (IEC CIM-aligned for electricity, water, gas) into client platforms, working with the wider practice and client data architects to align logical models, integration contracts, and physical implementations.
· Apply rigorous data modelling techniques (Kimball dimensional, Data Vault 2.0, canonical and conceptual modelling, semantic layers) appropriate to the workload and the consumption pattern, including serving layers feeding Power BI, Tableau, Qlik, and ThoughtSpot.
· Ensure platforms are AI-ready by design: feature stores, vector stores, retrieval-ready data products, and clean integration points with MLOps and LLMOps tooling (Azure ML, AWS SageMaker, Databricks ML, Microsoft Foundry) so that data science and AI workloads consume governed, traceable data.
· Embed data observability, lineage, data contracts, and quality controls into pipeline and platform design, working with the Data Governance Lead to integrate Microsoft Purview, Unity Catalog, Collibra, or equivalent catalogue and lineage tooling.
· Apply DataOps and DevOps engineering discipline across the delivery lifecycle: Git-based source control, CI/CD pipelines (Azure DevOps, GitHub Actions), infrastructure-as-code (Terraform, Bicep, CloudFormation), containerisation and orchestration (Docker, Kubernetes), and environment promotion practices.
· Contribute to nxzen IP development (e.g., nxzen's utility canonical data model, AI platform engineering, Field Knowledge Assistant, data foundations, accelerators and reference architectures for water, gas distribution, and electricity networks).
· Support pre-sales and business development by producing reference architectures, target operating model inputs, build-vs-buy assessments, proof-of-value prototypes, solution sizing, contributing to proposals, and participating in commercial
presentations, working under the direction of the Director of AI and Analytics and the UK Head of Data & AI.
· Apply responsible AI and platform risk management principles to platform design, including controls supporting model risk management, data residency, segregation, and alignment with the UK AI Regulation White Paper, NCSC Guidelines, and ISO/IEC 42001 where applicable.
· Lead delivery teams of data engineers, cloud engineers, and platform specialists on client engagements, including work allocation, technical direction, code and design review, architectural decision records, and supporting team members’ career development.
· Mentor more junior team members and support peer learning within the Data & AI practice, contributing to code review, design review, and technical standards development across the Global Capability Centre.
· Collaborate with onshore delivery leads and client data, infrastructure, and security teams through regular stand-ups, sprint planning, and technical reviews, operating effectively in a distributed onshore/offshore model across geographies and time zones.
· Stay current with advances in cloud data architecture and engineering (e.g., open table formats Iceberg/Delta/Hudi convergence, zero-copy data sharing, OneLake and cross-platform data fabrics, data contracts, Unified Namespace for OT, agentic data engineering, and serverless data processing), evaluating new approaches for applicability to nxzen’s client problems.
· Contribute to nxzen’s technical thought leadership in the cloud data architecture and data engineering space through internal knowledge sharing, technical blog posts, reusable solution accelerators, and partner co-marketing where relevant.
What we’re looking for
We are looking for a cloud data architect whose core strength is designing and engineering modern data platforms on multiple hyperscalers, with the ability to deliver end-to-end from architecture through to production. This is not an architecture-only role. We need someone who can take a client business problem, translate it into a pragmatic platform and integration design, build and deploy it with proper governance and observability, and lead a team doing the same. We expect at least 8 years of professional experience in cloud data architecture, data engineering, or related roles, with at least 5 years in hands-on design and delivery on hyperscaler platforms. A Bachelor’s degree in a quantitative or engineering discipline (Computer Science, Software Engineering, Information Systems, Mathematics, Physics, Engineering, or similar) is expected. A Master’s degree in a relevant field is desirable.
You will work in a distributed team with onshore/offshore consultants and client stakeholders in the UK and Australia. Strong written and spoken English is essential. You must be comfortable presenting technical architectures to non-technical audiences and working across time zones. Experience in energy, utilities, or infrastructure is highly desirable but not essential.
• Strong hands-on experience in at least two of the three major hyperscalers (Azure, AWS, GCP), with hyperscaler certifications expected for the primary cloud and desirable for the second. Examples: Azure Solutions Architect Expert and/or Azure Data Engineer Associate; AWS Solutions Architect Professional and/or AWS Data Engineer Associate; Google Cloud Professional Data Engineer and/or Professional Cloud Architect.
• Working knowledge of cloud landing zone design, networking, identity, security, encryption, key management, and cost management on at least two hyperscalers, aligned to Well-Architected Framework principles.
• At least 5 years designing and delivering modern data platforms in production on at least one of: Microsoft Fabric, Databricks, Snowflake, or a hyperscaler-native lakehouse stack (Synapse, Redshift, BigQuery). Strong working knowledge of Delta Lake, with familiarity of Iceberg and Hudi.
• Deep experience with modern architecture patterns including data lakehouse (with medallion layering), data mesh, data fabric, and data products. Able to select and justify the right pattern for the client's scale, maturity, and consumption needs.
• Strong data modelling skills across dimensional (Kimball), Data Vault 2.0, canonical and semantic modelling. Familiarity with industry canonical models (IEC CIM for electricity, MultiSpeak, ArcGIS Utility Network, or equivalents for water and gas) is highly desirable.
• Strong proficiency in Python and SQL for data engineering and platform automation, including hands-on experience with PySpark/Spark for distributed processing.
• Hands-on experience with data ingestion and orchestration tooling across batch, streaming, and change data capture, including at least: ADF/Synapse Pipelines, AWS Glue, GCP Dataflow, Airflow, dbt, and event streaming (Kafka, Event Hubs, Kinesis, or Pub/Sub).
• Experience with enterprise integration platforms in the nxzen toolset (Informatica IDMC/IICS/PowerCenter, MuleSoft, IBM ACE, WebMethods), including API-led design and event-driven architecture. Direct experience with at least two of these is required.
• Hands-on DevOps and DataOps experience: Git-based source control, CI/CD (Azure DevOps, GitHub Actions, GitLab), infrastructure-as-code (Terraform, Bicep, CloudFormation), containerisation (Docker) and basic Kubernetes literacy.
• Basic working knowledge of data governance: cataloguing, lineage, classification, masking, data contracts, and at least one governance tool (Microsoft Purview, Unity Catalog, Collibra, or Informatica CDGC). You will not lead governance, but your designs must integrate with it.
• Basic working knowledge of analytics and visualisation tooling (Power BI, Tableau, Qlik, ThoughtSpot, Grafana) sufficient to design serving and semantic layers that meet consumption requirements.
• Basic working knowledge of AI/ML platforms and tooling (Azure ML, AWS SageMaker, Databricks ML, Microsoft Foundry) and AI-ready data patterns including vector databases, feature stores, and retrieval-ready data products. Practical hands-on use of commercial LLMs (Claude, ChatGPT, Gemini) or open models (Llama, Mistral, Qwen) in your day-to-day engineering work is expected.
• At least 2 years leading data platform or engineering teams (formally or informally) on client engagements or internal projects, including work allocation, technical direction, design and code review, and supporting team members' development. Comfortable combining hands-on delivery with team leadership responsibilities.
• Strong written and spoken English. Comfortable presenting architectures and roadmaps to non-technical stakeholders, writing target operating models and architecture decision
records, contributing to proposals and commercial presentations, and participating in client-facing calls and workshops.
• Experience working with operational, asset, geospatial, or financial data in energy, utilities, or infrastructure sectors is highly desirable but not essential. Familiarity with SCADA, historian (AVEVA PI/OSIsoft), GIS (Esri), AMI/smart meter, or ERP/EAM data (SAP, Maximo) is a strong plus.
• Awareness of UK utilities regulatory data context (Ofgem RIIO, Ofwat AMP/PR24, CAF) and the implications for data residency, lineage, and audit is desirable but not essential.
• Genuine interest in energy, utilities, and critical national infrastructure as an application domain. Aligned to nxzen's purpose and brand.