Urwah Admin

Salt

<div>
 
 
 Customer Transformation Manager &ndash; Power &amp; Utilities
 
 
 
 
 Doha, Qatar
 
 
 
 
 Up to 25,000 QAR per month
 
 
 
 
 
 
 
 Are you passionate about helping organisations transform the way they engage with their customers
 
 
 
 
 
 ?
 
 My client are looking for an experience
 
 d Customer Transformation Manag
 
 er to join a leading consulting practice in Riyadh, working with some of the region's most prominent Power &amp; Utilities organisations. This is an exciting opportunity to drive large-scale customer transformation programmes, helping clients create customer-centric operating models, enhance service delivery, and leverage digital innovation to improve customer experience and business performanc
 
 
 e.The Opportuni
 
 
 
 
 
 ty
 
 As a Customer Transformation Manager, you will play a key role in shaping and delivering customer transformation strategies for major utilities organisations across the Middle East. Working closely with senior stakeholders, you will help organisations improve customer satisfaction, increase operational efficiency, and accelerate digital adoption through innovative customer-focused solutio
 
 
 
 
 
 ns.
 
 You will lead strategic transformation initiatives spanning customer experience, operating model design, digital channels, analytics, sustainability programmes, and customer engagem
 
 
 
 
 
 
 ent.
 
 Key Responsibil
 
 
 <ul>
 <li>
 itiesDevelop and deliver customer transformation strategies and roadmaps aligned to business object
 </li>
 <li>
 ives.Design and implement customer operating models across contact centres, digital channels, and key account management funct
 </li>
 <li>
 ions.Lead customer journey mapping exercises and identify opportunities to improve customer experience and service deli
 </li>
 <li>
 very.Drive customer-centric transformation initiatives across business and technology t
 </li>
 <li>
 eams.Monitor and improve customer performance metrics including customer satisfaction, digital adoption, and cost-to-s
 </li>
 <li>
 erve.Build customer intelligence capabilities through segmentation, analytics, and customer insight progra
 </li>
 <li>
 mmes.Support the design and delivery of customer-focused sustainability initiatives, including energy efficiency and demand-side management progra
 </li>
 <li>
 mmes.Develop innovative customer use cases leveraging AMI and smart metering technologies, including consumption insights, usage alerts, billing transparency, and demand response progra
 </li>
 <li>
 mmes.Support business development activities, proposal development, and client relationship manage
 </li>
 <li>
 ment.Engage with senior client stakeholders and act as a trusted advisor throughout transformation progra
 </li>
 </ul>
 
 
 
 
 
 mmes.
 
 Requir
 
 
 <ul>
 <li>
 ements10+ years of experience in customer transformation, customer experience, customer operations, or related discip
 </li>
 <li>
 lines.Strong experience within the Power &amp; Utilities s
 </li>
 <li>
 ector.Proven track record delivering large-scale customer transformation initia
 </li>
 <li>
 tives.Previous consulting experience within a Big 4 or leading management consulting
 </li>
 <li>
 firm.Experience designing customer operating models and customer journey transformation progr
 </li>
 <li>
 ammes.Strong understanding of customer analytics, segmentation, and customer intelligence capabil
 </li>
 <li>
 ities.Knowledge of digital customer channels, contact centre transformation, and customer service optimis
 </li>
 <li>
 ation.Familiarity with smart metering, AMI technologies, and customer-facing utility programmes is highly desi
 </li>
 <li>
 rable.Excellent stakeholder management and communication s
 </li>
 <li>
 kills.Demonstrated leadership experience managing teams and client engage
 </li>
 </ul>
 
 ments.Why
 
 <ul>
 <li>
 Apply?Work on some of the largest transformation programmes across the Middle
 </li>
 <li>
 East.Partner directly with senior executives and industry le
 </li>
 <li>
 aders.Drive innovation in customer experience, digital transformation, and sustainab
 </li>
 <li>
 ility.Join a globally recognised consulting organisation with exceptional career growth opportun
 </li>
 <li>
 ities.Be part of a collaborative and high-performing team shaping the future of the utilities s
 </li>
 </ul>
 
 
 
 ector.
</div>

Customer Transformation Manager

<div>
 
 ***HIRING*** - 3 Month Contract (Extendable)
 
 
 
 
 
 
 Job Title &ndash; Data Quality Engineer (Databricks).
 
 
 
 
 Salary &ndash; AED 35,000 - 38,000 Per Month.
 
 
 
 
 Contract Length &ndash; 3 Months &ndash; Extendable.
 
 
 
 
 Location &ndash; Dubai.
 
 
 
 
 Start Date &ndash; ASAP.
 
 
 
 
 
 
 
 Role Overview
 
 
 
 The Data Quality Engineer will be responsible for designing, implementing, and operating the client's enterprise data quality framework within the Databricks platform. The role will deliver automated profiling, quality rule execution, cleansing, monitoring, remediation support, and quality reporting capabilities across 170 datasets and 1,346 prioritised Critical Data Elements (CDEs).
 
 
 
 
 
 Working closely with Data Modellers, Data Catalogue Specialists, business data owners, and platform engineers, the Data Quality Engineer will establish scalable and reusable quality controls that improve trust, accuracy, completeness, consistency, timeliness, validity, and uniqueness across the client's data estate.
 
 
 
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 Databricks Platform Configuration and Administration
 
 
 <ul>
 <li>
 
 Configure and manage the Databricks environment supporting enterprise data quality operations.
 
 </li>
 <li>
 Establish and maintain:
 </li>
 <li>
 Compute clusters.
 </li>
 <li>
 PySpark notebook frameworks.
 </li>
 <li>
 Delta Lake storage structures.
 </li>
 <li>
 Unity Catalog integration.
 </li>
 <li>
 Optimise platform performance for large-scale profiling and rule execution across all in-scope datasets and CDEs.
 </li>
 <li>
 Implement development, testing, and production deployment standards for data quality assets.
 </li>
 </ul>
 
 
 
 
 
 Data Profiling and Quality Assessment
 
 
 <ul>
 <li>
 
 Design and develop AI-assisted profiling notebooks using PySpark.
 
 </li>
 <li>
 Perform baseline data quality assessments across the six quality dimensions:
 </li>
 <li>
 Completeness.
 </li>
 <li>
 Accuracy.
 </li>
 <li>
 Consistency.
 </li>
 <li>
 Validity.
 </li>
 <li>
 Timeliness.
 </li>
 <li>
 Uniqueness.
 </li>
 <li>
 Capture and analyse:
 </li>
 <li>
 Null value rates.
 </li>
 <li>
 Duplicate records.
 </li>
 <li>
 Invalid values.
 </li>
 <li>
 Format violations.
 </li>
 <li>
 Outliers.
 </li>
 <li>
 Schema drift.
 </li>
 <li>
 Produce quality profiling outputs for all prioritised CDEs and datasets.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Data Quality Rule Factory Development
 
 
 <ul>
 <li>
 
 Design and implement a reusable Data Quality Rule Factory.
 
 </li>
 <li>
 Build parameterised PySpark-based rule templates capable of supporting large-scale rule deployment.
 </li>
 <li>
 Enable automated generation and management of approximately 6,730 data quality rules without manual rule-by-rule development.
 </li>
 <li>
 Ensure rules are reusable, configurable, and maintainable across multiple datasets and domains.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Data Quality Controls and Pipeline Integration
 
 
 <ul>
 <li>
 Deploy quality rules as reusable Databricks Jobs integrated into Delta Lake processing pipelines.
 </li>
 <li>
 Embed quality controls within bronze, silver, and gold processing stages.
 </li>
 <li>
 Implement automated quality gates preventing data progression where defined thresholds are not met.
 </li>
 <li>
 Maintain rule traceability and execution history for audit and governance purposes.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Data Cleansing and Quality Improvement
 
 
 <ul>
 <li>
 Develop automated remediation and cleansing pipelines using PySpark.
 </li>
 <li>
 Implement:
 </li>
 <li>
 Standardisation routines.
 </li>
 <li>
 Data enrichment processes.
 </li>
 <li>
 Deduplication logic.
 </li>
 <li>
 Schema harmonisation controls.
 </li>
 <li>
 Deploy machine learning models managed through MLflow for:
 </li>
 <li>
 Anomaly detection.
 </li>
 <li>
 Exact duplicate detection.
 </li>
 <li>
 Fuzzy matching and duplicate identification.
 </li>
 <li>
 Ensure all AI and ML recommendations are explainable, auditable, and routed through human-in-the-loop validation processes where required.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Exception Management and Reprocessing
 
 
 <ul>
 <li>
 Design and manage exception handling processes for failed quality records.
 </li>
 <li>
 Implement quarantine Delta Lake tables serving as the Failed Record Register.
 </li>
 <li>
 Capture and maintain:
 </li>
 <li>
 Failure reason.
 </li>
 <li>
 Associated CDE.
 </li>
 <li>
 Rule reference.
 </li>
 <li>
 Processing timestamp.
 </li>
 <li>
 Resolution status.
 </li>
 <li>
 Develop reprocessing workflows to support correction and controlled re-ingestion of remediated records.
 </li>
 </ul>
 
 
 
 
 
 Data Quality Metrics and Reporting
 
 
 <ul>
 <li>
 Develop Delta Lake metric aggregation structures supporting enterprise quality reporting.
 </li>
 <li>
 Calculate and publish:
 </li>
 <li>
 Data Quality Index (DQI) scores.
 </li>
 <li>
 Dimension-level quality metrics.
 </li>
 <li>
 Rule pass/fail rates.
 </li>
 <li>
 Dataset compliance scores.
 </li>
 <li>
 SLA adherence indicators.
 </li>
 <li>
 Provide curated outputs to support Power BI quality dashboards and executive reporting.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Monitoring, Alerting and Predictive Quality Management
 
 
 <ul>
 <li>
 Configure automated quality monitoring and alerting mechanisms.
 </li>
 <li>
 Implement threshold-based notifications using:
 </li>
 <li>
 Databricks SQL Alerts.
 </li>
 <li>
 Azure Monitor integrations.
 </li>
 <li>
 Develop predictive risk scoring models to identify datasets at risk of future quality degradation.
 </li>
 <li>
 Support proactive quality management and operational intervention activities.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Root Cause Analysis and Remediation Support
 
 
 <ul>
 <li>
 Apply Databricks machine learning and pattern analysis techniques to profiling and rule execution outputs.
 </li>
 <li>
 Support AI-assisted root cause analysis across established remediation categories.
 </li>
 <li>
 Identify recurring quality issues, systemic defects, and process breakdowns.
 </li>
 <li>
 Produce prioritised remediation datasets for business and operational stakeholders.
 </li>
 <li>
 Export remediation outputs to Power BI and Excel to support:
 </li>
 <li>
 Remediation Tiering Matrix.
 </li>
 <li>
 Prioritisation Scoring Models.
 </li>
 <li>
 Governance reporting processes.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Governance, Compliance and Stakeholder Engagement
 
 
 <ul>
 <li>
 Collaborate with Data Modellers and Data Catalogue Specialists to ensure quality controls align with authoritative data definitions and metadata standards.
 </li>
 <li>
 Support DDA and DGE governance processes by producing required quality artefacts and evidence.
 </li>
 <li>
 Maintain documentation, version control, and audit trails for all quality assets, rules, models, and processes.
 </li>
 <li>
 Participate in quality reviews, governance forums, and stakeholder workshops.
 </li>
 </ul>
 
 
 
 
 
 Required Skills and Experience
 
 
 <ul>
 <li>
 Strong experience designing and implementing enterprise Data Quality frameworks.
 </li>
 <li>
 Advanced Databricks engineering experience.
 </li>
 <li>
 Strong PySpark development skills.
 </li>
 <li>
 Experience with:
 </li>
 <li>
 Delta Lake.
 </li>
 <li>
 Unity Catalog.
 </li>
 <li>
 Databricks Workflows and Jobs.
 </li>
 <li>
 Databricks SQL.
 </li>
 <li>
 Experience building scalable data validation and quality rule frameworks.
 </li>
 <li>
 Knowledge of machine learning techniques for anomaly detection and data quality monitoring.
 </li>
 <li>
 Experience using MLflow for model management and deployment.
 </li>
 <li>
 Strong understanding of data governance, metadata management, and data lifecycle processes.
 </li>
 <li>
 Experience integrating data quality metrics into reporting platforms such as Power BI.
 </li>
 <li>
 Knowledge of cloud-based data engineering and modern lakehouse architectures.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Deliverables
 
 
 <ul>
 <li>
 Configured Databricks Data Quality environment.
 </li>
 <li>
 Enterprise Data Quality Rule Factory.
 </li>
 <li>
 AI-assisted profiling notebooks and baseline assessment outputs.
 </li>
 <li>
 Automated data quality validation and gating processes.
 </li>
 <li>
 Data cleansing and remediation pipelines.
 </li>
 <li>
 Failed Record Register and reprocessing workflows.
 </li>
 <li>
 Data Quality metric aggregation tables.
 </li>
 <li>
 DQI reporting feeds and dashboard datasets.
 </li>
 <li>
 Predictive quality monitoring and alerting solutions.
 </li>
 <li>
 Root Cause Analysis and remediation support datasets.
 </li>
 <li>
 Governance, audit, and compliance artefacts supporting DDA and DGE reviews.
 </li>
 </ul>
 
 
 
 
 Regards,
 
 
 Ollie
 
 
 
 
</div>

Data Quality Engineer (Databricks)

<div>
 
 Head of Engineering / Lead DAML Developer
 
 
 Abu Dhabi, UAE | Remote Global Talent Considered
 
 
 
 
 
 I&rsquo;m currently partnering with a highly innovative early-stage blockchain business building a next-generation Real World Asset (RWA) tokenisation platform from the ground up.
 
 
 
 
 
 This is a genuinely rare opportunity to join at the very beginning of the journey as the founding engineering hire, helping architect, build, and scale an entirely new blockchain-native platform from inception.
 
 
 
 
 
 The business is focused on leveraging:
 
 
 &bull; DAML smart contract development
 
 
 &bull; Canton Network infrastructure
 
 
 &bull; Distributed ledger technologies
 
 
 &bull; Institutional-grade blockchain architecture
 
 
 &bull; Real World Asset tokenisation frameworks
 
 
 
 
 
 This is not a traditional corporate engineering role. This is a true 0&rarr;1 build environment where the successful individual will have significant ownership, autonomy, and influence across both the technical and strategic direction of the platform.
 
 
 
 
 
 You will be responsible for:
 
 
 &bull; Leading the end-to-end technical development of the platform
 
 
 &bull; Architecting scalable blockchain and distributed ledger infrastructure
 
 
 &bull; Designing and building DAML smart contract systems
 
 
 &bull; Driving backend engineering, integrations, security, scalability, and performance
 
 
 &bull; Working closely with founders and stakeholders on long-term product and engineering strategy
 
 
 &bull; Establishing engineering best practices and future technical direction
 
 
 &bull; Building and scaling the broader engineering team over time
 
 
 
 
 
 The environment would suit somebody who is:
 
 
 &bull; Deeply technical and hands-on
 
 
 &bull; Entrepreneurial in mindset
 
 
 &bull; Comfortable operating within ambiguity
 
 
 &bull; Passionate about blockchain innovation and distributed systems
 
 
 &bull; Excited by the challenge of building complex products from scratch
 
 
 &bull; Able to balance architecture, execution, and leadership simultaneously
 
 
 
 
 
 To be considered, strong commercial experience with DAML is essential, alongside experience working within blockchain infrastructure, distributed ledger ecosystems, or tokenisation-focused environments.
 
 
 
 
 
 Experience within institutional blockchain, Web3, digital assets, fintech infrastructure, or regulated financial environments would be highly advantageous.
 
 
 
 
 
 For the right individual, this is an opportunity to play a genuinely pivotal role in shaping what could become a highly significant platform within the evolving RWA and digital asset space.
 
 
 
 
 
 Remote global talent can be considered.
 
 
 
 
 
 If this sounds relevant to yourself, or somebody within your network, please feel free to reach out directly for a confidential conversation.
 
 
 
 
 
 #Blockchain #Web3 #DAML #Tokenisation #RWA #EngineeringLeadership #DistributedSystems #FinTech #SmartContracts #Hiring #AbuDhabi #Technology #Crypto #CantonNetwork #SoftwareEngineering #DigitalAssets
 
</div>

Head of Engineering

<div>
 
 
 Overview
 
 
 
 You are responsible for identifying, onboarding, and scaling high-demand brands across the portfolio. This is a demand-first role &mdash; grounded in data, not gut. You do not control pricing; you win by choosing the right brands, structuring the right partnerships, and scaling them fast.
 
 
 
 
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Identify high-demand brands using quantitative signals (search trends, marketplace data, social velocity, competitor benchmarking)
 </li>
 <li>
 Build a continuous pipeline of new brands across existing and new departments
 </li>
 <li>
 Lead end-to-end onboarding of brands &mdash; prioritizing marketplace and consignment models
 </li>
 <li>
 Structure commercial terms that minimize inventory risk and maximize assortment breadth
 </li>
 <li>
 Work with Digital, Content, and Marketing teams to launch and scale brands effectively
 </li>
 <li>
 Track brand performance (traffic, conversion, sell-through proxies, contribution) and act quickly
 </li>
 <li>
 Continuously refine the portfolio &mdash; onboard aggressively, prune ruthlessly
 </li>
 <li>
 Collaborate with supply chain and operations to ensure smooth onboarding and availability
 </li>
 <li>
 Support strategic outright buys only where justified by clear demand signals
 </li>
 </ul>
 
 
 
 
 
 What Good Looks Like
 
 
 <ul>
 <li>
 You consistently bring in brands customers are already searching for
 </li>
 <li>
 You reduce inventory risk while expanding assortment
 </li>
 <li>
 You move fast &mdash; onboarding in weeks, not months
 </li>
 <li>
 You think in data, not opinions
 </li>
 <li>
 Your portfolio feels fresh, relevant, and commercially sharp
 </li>
 </ul>
 
 
</div>

Oracle Fusion Solution Architect

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About Company

Customer Transformation Manager

Data Quality Engineer (Databricks)

Head of Engineering

Category Brand Manager

Oracle Fusion Solution Architect