ai engineer

architect

senior data engineer

architect engineer

senior engineer

enterprise architect data governance head

Masdar (Abu Dhabi Future Energy Company)

<div>
 Established in 2006, Masdar (Abu Dhabi Future Energy Company) is a global clean energy leader, transforming how the world produces and consumes energy through bold innovation and commercial excellence.
 
 
 Masdar is a clean energy investor, developer and operator, advancing renewable energy projects across key markets and technologies, with a global project portfolio capacity to date of over
 
 65
 
 gigawatts (GW).
 
 
 Jointly owned by
 
 TAQA, ADNOC and Mubadala
 
 , Masdar is driving the scale-up of renewables worldwide, targeting a portfolio capacity of 100GW by 2030.
 
 
 
 Job Description
 
 
 
 To supercharge this next decade of unprecedented growth, we are seeking a visionary Enterprise Architect to join the Chief Digitalization Officer&rsquo;s (CDO) Leadership Team.
 
 
 Reporting directly to the CDO, s/he/they will serve as the strategic architect and technical anchor for Masdar&rsquo;s global digital ecosystem. S/he/theywill spearhead the Enterprise Digital function, designing a flexible, best-of-breed composable architecture that seamlessly bridges modern corporate systems with agile, field-level renewable asset operations. Crucially, s/he/they will own and steer the global Data Management &amp; Data Governance strategy, defining the universal data taxonomies that transform cross-border operational insight into a competitive advantage.
 
 
 S/he/they will build up high-performing domain architects, to safeguard and scale our Digital Architecture and infrastructure, as well as a robust team of competent data management specialist. Masdar&rsquo;s future Enterprise Digital Architecture will empower Masdar to continue scaling and expanding securely, rapidly, and intelligently, and powering the world's clean energy future.
 
 
 
 Qualifications
 
 
 
 
 Minimum Requirements
 
 
 
 <ul>
 <li>
 15+ years of progressive experience operating at a global, enterprise-level architecture capacity, preferably within heavily asset-intensive or energy environments.
 </li>
 <li>
 10+ years of direct experience leading, managing, and developing a team of specialized domain architects.
 </li>
 <li>
 10+ years of hands-on experience in ERP and Data architecture design, with a proven track record of transitioning legacy setups into modern, composable designs.
 </li>
 <li>
 8+ years of experience architecting and managing global data management platforms.
 </li>
 <li>
 5+ years of dedicated experience driving Data Governance initiatives (establishing policies, frameworks, and master data hierarchies), as well sa running governing bodies.
 </li>
 <li>
 5+ years of people management and stakeholder management
 </li>
 <li>
 Strong &amp; clear Communicator who can translate complex technical design into business languages/value, while influencing peers and stakeholders for consensus.
 </li>
 <li>
 Ability of resolving design difference, prioritizing enterprise architecture design build-up into phases that matter to Masdar operations and efficiency.
 </li>
 <li>
 A collaborator and a team player, who can mentor and coach team members across the CDO team
 
 
 </li>
 </ul>
 
 Preferred &amp; Plus Factors
 
 
 
 <ul>
 <li>
 Prior experience with SAP S/4HANA ERP Core and O&amp;M (Operations &amp; Maintenance) global deployment.
 </li>
 <li>
 Deep familiarity with cybersecurity and industrial architectural frameworks specific to critical infrastructure (e.g., NIST, NERC CIP, or IEC 62443).
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 As part of the application process, we will collect, store and process personal information about you.
 
 
 Masdar will use your personal information in accordance with our
 
 Candidate Privacy Notice
 
 , which provides details on the purposes for which your data is processed.
</div>

Enterprise Architect & Data Governance Head

Masdar

<div>Company Description 
Established in 2006, Masdar (Abu Dhabi Future Energy Company) is a global clean energy leader, transforming how the world produces and consumes energy through bold innovation and commercial excellence.
Masdar is a clean energy investor, developer and operator, advancing renewable energy projects across key markets and technologies, with a global project portfolio capacity to date of over 65 gigawatts (GW).
Jointly owned by TAQA, ADNOC and Mubadala, Masdar is driving the scale-up of renewables worldwide, targeting a portfolio capacity of 100GW by 2030. 
Job Description 
To supercharge this next decade of unprecedented growth, we are seeking a visionary Enterprise Architect to join the Chief Digitalization Officer&rsquo;s (CDO) Leadership Team.
Reporting directly to the CDO, s/he/they will serve as the strategic architect and technical anchor for Masdar&rsquo;s global digital ecosystem. S/he/theywill spearhead the Enterprise Digital function, designing a flexible, best-of-breed composable architecture that seamlessly bridges modern corporate systems with agile, field-level renewable asset operations. Crucially, s/he/they will own and steer the global Data Management &amp; Data Governance strategy, defining the universal data taxonomies that transform cross-border operational insight into a competitive advantage.
S/he/they will build up high-performing domain architects, to safeguard and scale our Digital Architecture and infrastructure, as well as a robust team of competent data management specialist. Masdar&rsquo;s future Enterprise Digital Architecture will empower Masdar to continue scaling and expanding securely, rapidly, and intelligently, and powering the world's clean energy future. 
Qualifications 
Minimum Requirements<ul><li>
15+ years of progressive experience operating at a global, enterprise-level architecture capacity, preferably within heavily asset-intensive or energy environments.</li><li>
10+ years of direct experience leading, managing, and developing a team of specialized domain architects.</li><li>
10+ years of hands-on experience in ERP and Data architecture design, with a proven track record of transitioning legacy setups into modern, composable designs.</li><li>
8+ years of experience architecting and managing global data management platforms.</li><li>
5+ years of dedicated experience driving Data Governance initiatives (establishing policies, frameworks, and master data hierarchies), as well sa running governing bodies.</li><li>
5+ years of people management and stakeholder management</li><li>
Strong &amp; clear Communicator who can translate complex technical design into business languages/value, while influencing peers and stakeholders for consensus.</li><li>
Ability of resolving design difference, prioritizing enterprise architecture design build-up into phases that matter to Masdar operations and efficiency.</li><li>
A collaborator and a team player, who can mentor and coach team members across the CDO team</li></ul>
Preferred &amp; Plus Factors<ul><li>
Prior experience with SAP S/4HANA ERP Core and O&amp;M (Operations &amp; Maintenance) global deployment.</li><li>
Deep familiarity with cybersecurity and industrial architectural frameworks specific to critical infrastructure (e.g., NIST, NERC CIP, or IEC 62443).</li></ul> 

Additional Information<div></div> 
As part of the application process, we will collect, store and process personal information about you.
Masdar will use your personal information in accordance with our Candidate Privacy Notice, which provides details on the purposes for which your data is processed.</div>

Jorofy Private Limited

ENUM is Hiring in Oman | Enterprise System Architect &amp; Digital Transformation Consultant (On-Site)We are looking for a highly experienced professional to lead enterprise architecture and digital transformation initiatives across government and enterprise environments.Enterprise System Architect &amp; Digital Transformation ConsultantLocation: Oman (On-site)Key Skills &amp; Experience:✔ Enterprise Architecture &amp; Solution Design (TOGAF preferred) ✔ Microsoft .NET, Azure, Microservices &amp; API-first architecture ✔ AI/ML integration, LLMs, RAG, and intelligent systems design ✔ DevOps, CI/CD pipelines, Docker &amp; cloud-native practices ✔ Enterprise integration, system modernization &amp; governance ✔ Experience in government or large-scale enterprise projectsKey Responsibilities:✔ Design scalable and secure enterprise architectures ✔ Lead digital transformation and modernization initiatives ✔ Architect AI-enabled and data-driven platforms ✔ Define integration frameworks and technical standards ✔ Oversee end-to-end software engineering and deliveryInterested candidates may share their CV at: careers@enums.coCandidates with GCC or government project experience will be preferred.#Hiring #OmanJobs #EnterpriseArchitecture #DigitalTransformation #MicrosoftAzure #DotNet #AI #SystemArchitecture #TechnologyJobsEducation:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Enterprise Architecture &amp; Solution Design : 10 years (Required)</li></ul>Work Location: In person

Enterprise System Architect & Digital Transformation Consultant

ENEC Operations

<div>
 
 The Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance &amp; Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.
 
 
 
 
 
 The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.
 
 
 Activity: Data Engineering Architecture &amp; Platform Development
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
 
 
 &bull; Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools.
 
 
 &bull; Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs.
 
 
 &bull; Ensure seamless integration of OT and industrial data sources &mdash; including PI System, SCADA, and DCS &mdash; into enterprise data platforms.
 
 
 &bull; Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption.
 
 
 &bull; Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements.
 
 
 &bull; Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML.
 
 
 &bull; Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining &mdash; ensuring reliability and reproducibility.
 
 
 &bull; Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio.
 
 
 &bull; Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization.
 
 
 &bull; Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance.
 
 
 &bull; Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards.
 
 
 &bull; Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.
 
 
 Activity: Advanced Subject Matter Knowledge
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments.
 
 
 &bull; Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements.
 
 
 &bull; Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning.
 
 
 &bull; Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management.
 
 
 &bull; Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments.
 
 
 &bull; Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.
 
 
 Activity: Complex Problem Solving &amp; Innovation
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration &mdash; delivering innovative, compliant, and production-ready solutions.
 
 
 &bull; Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions.
 
 
 &bull; Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges.
 
 
 &bull; Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes.
 
 
 &bull; Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.
 
 
 &bull; Leads proof-of-concept and pilot initiatives to evaluate new data and AI technologies and engineering approaches
 
 
 
 
 
 Activity: Applied Skills &amp; Professional Know-How
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Expertly engineers, deploys, and operates scalable, secure, and compliant data and AI platforms across Databricks, Azure, and OT environments.
 
 
 &bull; Applies hands-on proficiency in building data pipelines, ML models, GenAI solutions, BI semantic models, and governance frameworks in production environments.
 
 
 &bull; Mentors and develops junior and mid-level data engineers, data scientists, and analytics engineers &mdash; building future-ready technical capabilities.
 
 
 &bull; Leads technical design reviews, code reviews, and architecture assessments to uphold engineering quality and best practices.
 
 
 &bull; Effectively translates complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
 
 
 &bull; Documents solutions, engineering patterns, and technical standards to build institutional knowledge and enable knowledge transfer.
 
 
 Activity: Security, Governance &amp; Compliance
 
 
 
 
 
 Responsibilities and Accountabilities:
 
 
 &bull; Design and enforce data security, access control, and privacy frameworks across all data and AI platforms using Unity Catalog, Collibra, and Azure security controls.
 
 
 &bull; Ensure all data engineering and AI solutions comply with national and international nuclear regulations, FANR requirements, and Responsible AI principles.
 
 
 &bull; Maintain comprehensive data lineage, audit trails, and documentation to support regulatory, audit, and governance requirements.
 
 
 &bull; Implement and enforce data quality frameworks and data governance policies using Collibra Data Quality and Unity Catalog.
 
 
 &bull; Conduct regular platform security assessments, data quality audits, and compliance reviews.
 
 
 &bull; Oversee risk management, audit readiness, and the implementation of robust technical controls for all platform operations.
 
 
 
 
 
 
 
 
 
 Minimum
 
 
 
 &bull; Bachelor&rsquo;s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.
 
 
 &bull; Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations.
 
 
 &bull; Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.
 
 
 
 
 
 
 
 
 
 Preferred
 
 
 
 
 
 
 &bull; Master&rsquo;s degree in a relevant field.
 
 
 &bull; Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors.
 
 
 &bull; Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in data bricks or similar AI/analytics platforms exposure.
 
 
 &bull; Demonstrated experience leading large-scale data and AI engineering programs
 
 
 
 
 
 
 
 
 
 Certification -
 
 
 
 
 
 
 Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.
 
 
 
 
 
 Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).
 
</div>

Data and AI Engineering Expert

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

Xebia

<div>
 
 We are seeking a
 
 Databricks Architect
 
 with deep expertise in
 
 Azure Data Platform, Data Modelling, and Medallion (Lakehouse) Architecture
 
 . The ideal candidate will design and implement scalable, high-performance data solutions using
 
 Databricks, Delta Lake, and modern data engineering practices
 
 , enabling enterprise-wide analytics and business intelligence.
 
 
 
 
 
 
 Location:
 
 Abu Dhabi
 
 
 
 Experience:
 
 10&ndash;15+ Years
 
 
 
 Email
 
 : vijay.kajla@xebia.com
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 Medallion Architecture &amp; Lakehouse Design
 
 
 <ul>
 <li>
 Design and implement
 
 Medallion Architecture (Bronze, Silver, Gold layers)
 
 on
 
 Azure Databricks
 
 </li>
 <li>
 Define data flow standards across ingestion, cleansing, transformation, and consumption layers
 </li>
 <li>
 Ensure
 
 data quality, lineage, and governance
 
 across all layers
 </li>
 <li>
 Optimize storage and compute using
 
 Delta Lake features (ACID transactions, time travel, schema evolution)
 
 </li>
 </ul>
 
 
 Architecture &amp; Strategy
 
 
 <ul>
 <li>
 Architect
 
 end-to-end Azure data platforms
 
 using:
 </li>
 <li>
 Azure Databricks
 </li>
 <li>
 ADLS Gen2
 </li>
 <li>
 Azure Data Factory
 </li>
 <li>
 Azure Synapse
 </li>
 <li>
 Define
 
 data platform standards, best practices, and reusable frameworks
 
 </li>
 <li>
 Lead
 
 data modernization initiatives
 
 (on-prem to cloud, legacy to lakehouse)
 </li>
 </ul>
 
 
 Data Engineering Leadership
 
 
 <ul>
 <li>
 Build scalable pipelines using
 
 PySpark, Spark SQL, and Databricks workflows
 
 </li>
 <li>
 Implement
 
 batch + real-time ingestion patterns
 
 </li>
 <li>
 Drive
 
 performance tuning and cost optimization
 
 </li>
 <li>
 Mentor teams on
 
 Spark optimization, partitioning, and job orchestration
 
 </li>
 </ul>
 
 
 Data Modelling
 
 
 <ul>
 <li>
 Design
 
 enterprise-grade data models
 
 :
 </li>
 <li>
 Dimensional (Star/Snowflake)
 </li>
 <li>
 Normalized and Data Vault (nice to have)
 </li>
 <li>
 Align data models with
 
 Gold layer consumption use-cases (BI/Reporting)
 
 </li>
 <li>
 Translate business needs into
 
 scalable analytical datasets
 
 </li>
 </ul>
 
 
 Integration &amp; Consumption
 
 
 <ul>
 <li>
 Build ingestion pipelines using:
 </li>
 <li>
 
 ADF, Event Hub, Kafka, APIs
 
 </li>
 <li>
 Enable reporting via:
 </li>
 <li>
 
 Power BI, Tableau, or similar BI tools
 
 </li>
 <li>
 Ensure seamless consumption from
 
 Gold datasets
 
 </li>
 </ul>
 
 
 Stakeholder Engagement
 
 
 <ul>
 <li>
 Act as a
 
 data architecture SME
 
 in client discussions
 </li>
 <li>
 Drive solutioning, architecture reviews, and governance forums
 </li>
 <li>
 Collaborate with business teams for
 
 data-driven decision making
 
 </li>
 </ul>
 
 
 Required Skills
 
 
 
 
 Core
 
 
 <ul>
 <li>
 Strong hands-on experience with
 
 Azure Databricks &amp; Delta Lake
 
 </li>
 <li>
 Proven expertise in
 
 Medallion Architecture implementation
 
 </li>
 <li>
 Advanced
 
 PySpark and Spark SQL
 
 </li>
 <li>
 Experience with
 
 ADF, ADLS Gen2, Synapse
 
 </li>
 </ul>
 
 
 Data Modelling
 
 
 <ul>
 <li>
 Strong experience in:
 </li>
 <li>
 
 Dimensional modelling (must-have)
 
 </li>
 <li>
 Data modelling aligned to
 
 Gold layer analytics
 
 </li>
 <li>
 Understanding of
 
 data quality and governance frameworks
 
 </li>
 </ul>
 
 
 Nice-to-Have
 
 
 <ul>
 <li>
 Real-time processing (
 
 Kafka / Spark Streaming
 
 )
 </li>
 <li>
 Azure Purview or data governance tools
 </li>
 <li>
 ML pipelines on Databricks
 </li>
 <li>
 Domain: Airlines / BFSI / Retail
 </li>
 </ul>
 
 
 Leadership Skills
 
 
 <ul>
 <li>
 Strong architectural thinking
 </li>
 <li>
 Client-facing experience
 </li>
 <li>
 Ability to lead and scale engineering teams
 </li>
 <li>
 Excellent communication and stakeholder management
 </li>
 </ul>
 
 
 
 
 We are an Equal Opportunity Employer committed to fostering a diverse, inclusive, and respectful workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We believe diversity drives innovation and success, and we welcome individuals from all backgrounds to join our team.
 
</div>

Data Architect

Sprinklr

<div>
 Sprinklr is the definitive, AI-native platform for Unified Customer Experience Management (Unified-CXM), empowering brands to deliver extraordinary experiences at scale &mdash; across every customer touchpoint.
 
 
 By combining human instinct with the speed and efficiency of AI, Sprinklr helps brands earn trust and loyalty through personalized, seamless, and efficient customer interactions. Sprinklr&rsquo;s unified platform provides powerful solutions for every customer-facing team &mdash; spanning social media management, marketing, advertising, customer feedback, and omnichannel contact center management &mdash; enabling enterprises to unify data, break down silos, and act on real-time insights.
 
 
 Today, 1,900+ enterprises and 60% of the Fortune 100 rely on Sprinklr to help them deliver consistent, trusted customer experiences worldwide.
 
 
 
 Job Description
 
 
 
 
 Lead Solutions Architect &ndash; Platform, Data &amp; AI
 
 
 
 Sprinklr seeks a Lead Solutions Architect &ndash; Platform, Data, AI &amp; Integrations to partner with sales, product, and customer success to drive revenue by architecting, demonstrating, and operationalizing Sprinklr&rsquo;s Unified-CXM platform across enterprise technology, customer data, knowledge, and AI ecosystems.
 
 
 Solution Architects at Sprinklr combine deep technical expertise with strategic business consulting to uncover customer needs and position Sprinklr&rsquo;s platform, integration, customer data, knowledge, and AI capabilities. They provide trusted advisory guidance and rapidly map customer architectures across enterprise systems, customer data layers, knowledge frameworks, governance models, and emerging agentic AI ecosystems.
 
 
 This role focuses on Sprinklr&rsquo;s platform integration layer, customer data architecture, knowledge and experience design, enterprise AI/ML alignment, and agentic orchestration capabilities &mdash; including connector ecosystems, native import/export workflows, open APIs, unified customer intelligence, knowledge activation, automation, and intelligent autonomous workflows.
 
 
 
 What You'll Do
 
 
 
 
 Platform, Integration &amp; Customer Data Architecture
 
 
 
 <ul>
 <li>
 Architect end-to-end platform, customer data, knowledge, and integration solutions leveraging Sprinklr&rsquo;s connector ecosystem, unified customer intelligence frameworks, native import/export capabilities, knowledge systems, and REST API ecosystem.
 </li>
 <li>
 Design enterprise customer data architectures including customer identity resolution, profile unification, source-agnostic ingestion, structured/unstructured data harmonization, segmentation frameworks, consent and governance layers, customer memory, and omnichannel data continuity.
 </li>
 <li>
 Develop customer knowledge and experience architectures that activate operational, behavioral, conversational, and contextual customer intelligence across AI, service, marketing, and customer engagement workflows.
 </li>
 <li>
 Present enterprise architecture blueprints for common patterns &mdash; including CRM lifecycle integration, CDP synchronization, DAM connectivity, customer knowledge activation, omnichannel handover, case and interaction history continuity, reporting/analytics extraction, and platform extensibility.
 
 
 </li>
 </ul>
 
 AI, Agentic &amp; Knowledge Leadership
 
 
 
 <ul>
 <li>
 Lead AI, knowledge, and agentic solution design by mapping customer ecosystems to Sprinklr AI+, conversational AI, LLM ecosystems, enterprise search, RAG frameworks, NLP engines, memory architectures, and autonomous workflow orchestration.
 </li>
 <li>
 Define architectures for agentic enterprise use cases such as AI copilots, autonomous customer service agents, knowledge assistants, intelligent routing, AI-driven workflow execution, retrieval-augmented generation (RAG), customer memory systems, and real-time decision intelligence.
 </li>
 <li>
 Design knowledge governance frameworks including content ingestion, semantic search, taxonomy design, vectorization strategies, metadata structures, knowledge lifecycle management, and enterprise-safe AI deployment.
 </li>
 <li>
 Advise on AI + customer data governance including guardrails, hallucination mitigation, memory controls, observability, consent frameworks, model governance, and human-in-the-loop safety.
 
 
 </li>
 </ul>
 
 Presales Discovery, Consulting &amp; Transformation
 
 
 
 <ul>
 <li>
 Lead strategic discovery workshops to assess customer technology stacks, customer data maturity, AI readiness, and enterprise transformation opportunities across CRM, CDP, ERP, martech, DAM, analytics, cloud, compliance, and AI ecosystems.
 </li>
 <li>
 Map customer current-state ecosystems into Sprinklr&rsquo;s unified platform, customer data, knowledge, and AI architecture while producing fit-gap analyses, phased transformation strategies, and extensibility roadmaps.
 </li>
 <li>
 Develop and deliver compelling technical demonstrations, AI showcases, and Proofs of Concept (POCs)highlighting customer data activation, bi-directional integration, knowledge orchestration, API-led extensibility, agentic AI, and unified customer experiences.
 </li>
 <li>
 Translate fragmented architectures into strategic business outcomes by identifying operational inefficiencies, customer experience gaps, AI opportunities, and transformation priorities.
 
 
 </li>
 </ul>
 
 Strategic Advisory &amp; Thought Leadership
 
 
 
 <ul>
 <li>
 Provide strategic guidance on enterprise architecture spanning authentication, customer identity, data governance, transformation pipelines, compliance, observability, rate management, knowledge governance, and AI safety.
 </li>
 <li>
 Collaborate across Sprinklr&rsquo;s product, platform, AI, architecture, and sales ecosystem to validate designs against current capabilities and future roadmap priorities.
 </li>
 <li>
 Support RFPs, executive presentations, and technical strategy related to platform design, customer data architecture, AI transformation, knowledge governance, security, and compliance.
 </li>
 <li>
 Serve as a subject matter expert on Sprinklr&rsquo;s platform + customer data + knowledge + AI + integration taxonomy, clearly articulating the value of unified architectures over fragmented ecosystems.
 </li>
 <li>
 Act as a trusted technical advisor to CIOs, Chief Digital Officers, Chief Data Officers, enterprise architects, AI leaders, and transformation teams by translating complex technical ecosystems into measurable business value.
 
 
 </li>
 </ul>
 
 Travel
 
 
 
 <ul>
 <li>
 Travel up to 40% for customer engagements, strategic workshops, partner enablement, executive advisory sessions, and industry events.
 
 
 </li>
 </ul>
 
 Education &amp; Experience
 
 
 
 
 Who You Are &amp; What Makes You Qualified
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Science, Information Systems, Engineering, or related field; Master&rsquo;s degree preferred.
 </li>
 <li>
 7+ years of experience in enterprise platform architecture spanning integrations, customer data, AI, knowledge systems, or cloud ecosystems.
 </li>
 <li>
 5+ years of experience architecting and demonstrating enterprise solutions in presales, solutions engineering, technical consulting, or transformation leadership roles with measurable revenue impact
 
 
 </li>
 </ul>
 
 Platform, Integration &amp; Technical Depth
 
 
 
 <ul>
 <li>
 Deep expertise in enterprise integration patterns including REST/GraphQL APIs, webhook orchestration, event-driven architecture, ETL/ELT pipelines, source-agnostic ingestion, identity systems, API gateways, and bi-directional SaaS connectivity.
 </li>
 <li>
 Hands-on experience with enterprise SaaS ecosystems including CRM, CDP, DAM, workforce management, analytics, martech, customer feedback, and operational systems.
 </li>
 <li>
 Strong proficiency with integration tooling and standards including OAuth 2.0, SAML/SSO, JSON/XML, iPaaS platforms, middleware, cloud integration ecosystems, and governance frameworks.
 </li>
 <li>
 Customer Data Architecture &amp; Knowledge Systems
 </li>
 <li>
 Deep expertise in customer data architecture and enterprise knowledge design, including customer identity resolution, profile unification, master data alignment, metadata strategy, taxonomy design, knowledge graphs, and structured/unstructured data harmonization across CX, CRM, CDP, and service ecosystems.
 </li>
 <li>
 Proven experience architecting customer knowledge and experience frameworks that unify operational, behavioral, conversational, and contextual data to power personalized journeys, AI copilots, agentic workflows, retrieval-augmented generation (RAG), and enterprise search.
 </li>
 <li>
 Strong understanding of customer experience data models including journey orchestration, interaction history, case lifecycle, segmentation, consent, privacy, customer memory, and omnichannel continuity.
 </li>
 <li>
 Hands-on experience designing enterprise knowledge architectures supporting content governance, ingestion pipelines, semantic search, vectorization strategies, metadata frameworks, knowledge lifecycle management, and real-time decision intelligence.
 </li>
 <li>
 Ability to transform fragmented ecosystems into a unified customer data + knowledge + experience architecturethat improves customer outcomes, AI accuracy, operational efficiency, and platform scalability.
 
 
 </li>
 </ul>
 
 AI, Agentic &amp; Data Intelligence
 
 
 
 <ul>
 <li>
 Strong knowledge of AI/ML, Generative AI, and agentic architectures including LLMs, NLP, RAG, enterprise search, vector systems, orchestration frameworks, memory systems, autonomous agents, and intelligent workflow automation.
 </li>
 <li>
 Experience designing agentic systems with governance, observability, trust layers, guardrails, lifecycle management, and enterprise-safe deployment strategies.
 </li>
 <li>
 Familiarity with cloud data ecosystems such as Snowflake, Databricks, AWS, Azure, GCP, or equivalent enterprise data intelligence platforms.
 
 
 </li>
 </ul>
 
 Business Consulting &amp; Leadership
 
 
 
 <ul>
 <li>
 Strong capability to perform deep discovery across customer architecture, customer data maturity, AI readiness, and operational transformation needs while aligning phased adoption strategies.
 </li>
 <li>
 Excellent communication skills with the ability to influence enterprise architects, CIOs, CDOs, IT decision-makers, and C-suite executives by translating platform, data, AI, and customer experience architectures into business outcomes.
 </li>
 <li>
 Experience contributing to thought leadership, sales enablement, partner ecosystem growth, strategic transformation, and innovation programs.
 
 
 </li>
 </ul>
 
 Governance, Privacy &amp; Security
 
 
 
 <ul>
 <li>
 Strong knowledge of security, privacy, compliance, and responsible AI frameworks including SOC 2, GDPR, CCPA, customer consent frameworks, governance-by-design, and enterprise-safe customer data activation.
 
 
 </li>
 </ul>
 
 Ideal Differentiators
 
 
 
 <ul>
 <li>
 Experience with conversational AI, autonomous enterprise agents, customer memory systems, or enterprise AI transformation.
 </li>
 <li>
 Familiarity with CCaaS, CXM, customer service transformation, and unified customer engagement ecosystems.
 </li>
 <li>
 Ability to position Sprinklr as more than a platform &mdash; as a Unified Customer Experience, Customer Data, Knowledge, and Agentic AI Transformation Architecture.
 </li>
 <li>
 Passion for shaping the future of enterprise customer engagement through platform unification, customer intelligence, and autonomous AI innovation.
 
 
 </li>
 </ul>
 
 We focus on our mission
 
 : Sprinklr was founded in 2009 to solve a big problem: growing enterprise complexity that separated brands from their customers. Our vision was clear: to unify fragmented teams, tools and data &mdash; helping large organizations build deeper, more meaningful connections with the people they serve. Today, Sprinklr has a unified, AI-native platform for four product suites: Sprinklr Service, Sprinklr Social, Sprinklr Marketing, and Sprinklr Insights. Sprinklr is here to do three things:
 
 
 <ul>
 <li>
 Lead a new category of enterprise software that we call Unified-CXM.
 </li>
 <li>
 Empower companies to deliver next generation, unified engagement journeys that reimagine the customer experience.
 </li>
 <li>
 Create a culture of customer obsession, with trust, teamwork, and accountability.
 
 
 </li>
 </ul>
 
 We believe in our product
 
 : Customers who value exceptional customer experiences have what they need on our single unified platform, built with an operating system approach on a single codebase. That means that everything &mdash; and everyone &mdash; can work together to service, respond, sell, and market to customers on the channels they prefer. While Unified Customer Experience Management (Unified-CXM) as a category is just getting started, we are well on our way to creating a no-compromise, unified approach to better customer experiences for the world&rsquo;s leading enterprise brands.
 
 
 
 We invest in our people
 
 : We offer a comprehensive suite of benefits designed to help each member of our team thrive. Sprinklr believes that you should be able to get the type of care you need for your personal well-being when you need it. We offer you and your family voluntary healthcare coverage in countries where applicable. We believe it is important to take time off &ndash; it is essential for your mental and physical wellbeing. We provide Sprinklrites with paid time off to recharge and spend time with loved ones. We want to grow our talent with purpose. Our open Mentoring Program is designed to create meaningful connections that support growth and amplify our focus.
 
 
 To learn more about employee benefits by region, click here.
 
 
 To learn more about all-things-Sprinklr, visit our candidate resource hub here.
 
 
 
 EEO - Our philosophy
 
 : Our goal is to ensure every employee feels like they belong and are operating in a collaborative environment. We fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we&rsquo;re more innovative, creative, and successful.
 
 
 Sprinklr is proud to be an equal-opportunity workplace and complies with all applicable federal, state, and local fair employment practices laws. We are committed to equal employment opportunity regardless of race, color, religion, creed, national origin or ancestry, ethnicity, sex (including gender, pregnancy, sexual orientation, and gender identity), age, physical or mental disability, citizenship, past, current, or prospective service in the uniformed services, genetic information, or any other characteristic protected under applicable law.
 
 
 Reasonable accommodations are available upon request during the interview process. To request an accommodation, please work directly with your recruitment coordinator or recruiter.
 
 
 
 Warning about Recruiting Scams:
 
 Please be vigilant for recruiting scams impersonating Sprinklr. Sprinklr will never ask you for money, to pay for equipment, or for unnecessary personal information during the interview process. Sprinklr will also never pay in Bitcoin or send email communications from our executives. Please review the Federal Trade Commission's advice to avoid these types of scams.
 
 
 If you are contacted by someone whom you suspect may not be appropriately representing Sprinklr, please do not engage and block their email or phone number immediately.
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