qa/qc engineer

estimation engineer

ai engineer

applied ai engineer

data engineer

data quality engineer databricks

Datamatics Global Services Ltd

<div>Job Description &ndash; Data Quality Engineer (Databricks) &ndash; x 4 Positions 
Location: Abudhabi - UAE - Onsite 
Open to Relocate 
Duration: 6 months ( Extendable to One Year) 
Experience: 5 to 7 Years 
Project start date is 1st July - Immediate joiners will be preferred 
 
Role Overview 
The Data Quality Engineer will be responsible for designing, implementing, and operating ADC'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 ADC'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:<ul><li>
Compute clusters.</li><li>
PySpark notebook frameworks.</li><li>
Delta Lake storage structures.</li><li>
Unity Catalog integration.</li></ul></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:<ul><li>
Completeness.</li><li>
Accuracy.</li><li>
Consistency.</li><li>
Validity.</li><li>
Timeliness.</li><li>
Uniqueness.</li></ul></li><li>
Capture and analyse:<ul><li>
Null value rates.</li><li>
Duplicate records.</li><li>
Invalid values.</li><li>
Format violations.</li><li>
Outliers.</li><li>
Schema drift.</li></ul></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:<ul><li>
Standardisation routines.</li><li>
Data enrichment processes.</li><li>
Deduplication logic.</li><li>
Schema harmonisation controls.</li></ul></li><li>
Deploy machine learning models managed through MLflow for:<ul><li>
Anomaly detection.</li><li>
Exact duplicate detection.</li><li>
Fuzzy matching and duplicate identification.</li></ul></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:<ul><li>
Failure reason.</li><li>
Associated CDE.</li><li>
Rule reference.</li><li>
Processing timestamp.</li><li>
Resolution status.</li></ul></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:<ul><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></ul></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:<ul><li>
Databricks SQL Alerts.</li><li>
Azure Monitor integrations.</li></ul></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:<ul><li>
Remediation Tiering Matrix.</li><li>
Prioritisation Scoring Models.</li><li>
Governance reporting processes.</li></ul></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:<ul><li>
Delta Lake.</li><li>
Unity Catalog.</li><li>
Databricks Workflows and Jobs.</li><li>
Databricks SQL.</li></ul></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>
dmGrkjT88v</div>

Data Quality Engineer (Databricks)

Dicetek LLC

<div>
 Role Overview
 
 
 We are seeking a highly skilled and motivated Data Engineer with 5&ndash;7 years of experience to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong expertise in SQL, Databricks, Confluent (Kafka), Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS), with a solid understanding of banking domain processes and regulatory considerations. This role involves working closely with cross-functional teams to enable data-driven decision-making across critical banking functions.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain robust, scalable data pipelines using Azure Data Factory (ADF) and Databricks
 </li>
 <li>
 Implement batch and real-time data ingestion frameworks leveraging Confluent Kafka
 </li>
 <li>
 Build and optimize data models, transformations, and ETL/ELT pipelines using SQL and Spark
 </li>
 <li>
 Develop and manage data storage solutions in Azure Data Lake Storage (ADLS)
 </li>
 <li>
 Ensure high data quality, integrity, and governance standards
 </li>
 <li>
 Support data integration across systems including core banking and CRM
 </li>
 <li>
 Optimize performance of large-scale datasets
 </li>
 <li>
 Collaborate with stakeholders to translate requirements into solutions
 </li>
 <li>
 Ensure compliance with banking regulations and data privacy
 </li>
 <li>
 Troubleshoot production issues
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Strong expertise in SQL (complex queries, tuning, modeling)
 </li>
 <li>
 Hands-on experience with Databricks, Spark, PySpark
 </li>
 <li>
 Experience with Confluent Kafka and event-driven architecture
 </li>
 <li>
 Experience with Azure Data Factory (ADF)
 </li>
 <li>
 Experience with Azure Data Lake Storage (ADLS)
 </li>
 <li>
 Understanding of data warehousing concepts
 </li>
 <li>
 Familiarity with CI/CD and DevOps for data platforms
 
 
 </li>
 </ul>
 
 Domain Knowledge (Preferred)
 
 
 
 <ul>
 <li>
 Experience in banking or financial services
 </li>
 <li>
 Understanding of core banking systems
 </li>
 <li>
 Knowledge of payments, lending, wealth management
 </li>
 <li>
 Awareness of regulatory frameworks (KYC, AML)
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong analytical and problem-solving skills
 </li>
 <li>
 Excellent communication and stakeholder engagement
 </li>
 <li>
 Ability to work in fast-paced environments
 </li>
 <li>
 Strong ownership and collaboration mindset
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in relevant field
 </li>
 <li>
 Azure/Data engineering certifications preferred
 
 
 </li>
 </ul>
 Good to Have
 
 
 <ul>
 <li>
 Experience with Python or Scala
 </li>
 <li>
 Exposure to data governance tools
 </li>
 <li>
 Knowledge of APIs and microservices
 </li>
 <li>
 Experience with BI tools like Power BI
 </li>
 </ul>
</div>

Data Engineer

KAYALI

<div>Who We Are
Fueled by passion, KAYALI was founded in 2018 by beauty mogul and fragrance fanatic, Mona Kattan. Translating to &lsquo;my imagination&rsquo; in Arabic, KAYALI provides a modern fragrance experience inspired by Mona&rsquo;s rich Middle Eastern heritage and the art of layering scents to help you create your mood; where sharing scents is a ritual and smelling good is both an act of goodwill and self-love. Mona collaborates with some of the world&rsquo;s most renowned perfumers and sources the finest ingredients to create unique juices that are infinitely memorable, long-lasting, and cruelty-free. Each luxurious fragrance is an ode to true craftsmanship and tells a special story, from the addictive notes to the multi-faceted jeweled bottles. 
Our Mission
To make everyone feel like the diamond they are! To build a global community of fragrance lovers through the power of scent and by providing them with the most innovative &amp; luxurious fragrances, education and sharing our Middle Eastern fragrance rituals with the world. 
Summary
Introduction of a new role to provide expertise across data warehousing platforms including Azure Data Bricks and Power BI along with all the necessary integrations. The BI Engineer will be responsible for supporting, implementing and maintaining data warehouse Pipelines and Reports to streamline business process. 
RESPONSIBILITIES:
Data Platform &amp; Architecture<ul><li>
Manage a scalable modern Data platform leveraging the Azure ecosystem, including Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and Azure Data Lake Storage.
</li><li>Design and implement Lakehouse architecture using Medallion (Bronze, Silver, Gold) patterns with Delta Lake to ensure data reliability, scalability, and performance with knowledge of Delta Lake and ACID-compliant data architectures
</li><li>Apply data modelling techniques (dimensional modelling, star/snowflake schemas) to support both operational and analytical use cases.</li></ul>
Data Engineering &amp; Pipelines<ul><li>
Develop and maintain robust, high-performance data pipelines using cloud-native technologies (Databricks, PySpark, Lakehouse Workflows) to support ingestion, transformation, and curation of large-scale datasets.
</li><li>Knowledge in identifying and resolving complex data discrepancies across multi-stage ETL/ELT pipelines, with a focus on root cause analysis (RCA) of failures, data skew, and late-arriving data etc.
</li><li>Build and optimize end-to-end data integration frameworks, including ingestion from relational databases, flat files, and third-party REST APIs (handling authentication, pagination, and incremental loads).
</li><li>Troubleshoot and resolve complex data pipeline failures, performance bottlenecks, and data inconsistencies, performing root cause analysis in production environments.</li></ul>
Business Intelligence &amp; Power BI<ul><li>
Design, develop, and optimize Power BI datasets, reports, and dashboards, applying best practices in data modelling, DAX, and performance tuning.
</li><li>High-level proficiency in performance tuning and semantic model debugging, specifically using tools like DAX Studio and Tabular Editor to isolate issues within the Filter Context, Row Context, and complex relationship cardinalities.
</li><li>Strategic ability to troubleshoot data issues and investigate Gateway connectivity failures, Direct Query latency issues, and visual-level calculation errors to ensuring report accuracy and faster response times for executive stakeholders.</li></ul>
Data Integration &amp; Consumption<ul><li>
Manage the integration of data platforms with Power BI, ensuring efficient data models and seamless data consumption for reporting and analytics.</li></ul>
Data Governance &amp; Security<ul><li>
Implement and manage data security frameworks, including role-based access control (RBAC), Row-Level Security, and governance using Unity Catalog or equivalent tools.</li></ul>
DevOps, CI/CD &amp; Deployment<ul><li>
Knowledge in CI/CD pipelines using Azure DevOps or GitHub Actions to enable automated, reliable, and consistent deployment of data solutions.</li></ul>
Performance Optimization &amp; Cost Management<ul><li>
Monitor and optimize data platform performance and cloud resource utilization, identifying cost optimization opportunities and ensuring efficient workload execution.</li></ul>
Data Quality &amp; Reliability<ul><li>
Implement data quality, validation, and monitoring frameworks to ensure accuracy, consistency, and reliability of data assets.</li></ul>
Stakeholder Collaboration &amp; Delivery<ul><li>
Collaborate with cross-functional teams including business stakeholders, analysts, and engineers to translate business requirements into scalable technical solutions.</li></ul> 

Requirements 
<ul><li>
 Minimum 5+ years in both Reporting and Data engineering domain, with at least 3+ years focused on Azure based data platforms mainly Power BI and Azure Databricks.</li><li>
 Comprehensive knowledge of the Azure Data Stack and Strong hands-on experience with Azure Databricks, Azure Data Lake Storage, Synapse, ADF and open-source cloud native tools.</li><li>
 Extensive experience in Power BI, including Dataset design and optimization, Report and dashboard development using calculated measures, DAX etc.</li><li>
Knowledge of performance tuning techniques (Query optimization, Import vs Direct Query, aggregations etc).</li><li>
Proficiency in SQL, PySpark, Python</li><li>
 Solid understanding on Data modelling techniques.</li><li>
 Effective problem-solving skills backed by strong people skills.</li><li>
 Excellent oral and written communication skills.</li></ul> 

Benefits 
<ul><li>
Premium Medical/Dental/Vision coverage</li><li>
Find your Magic Days</li><li>
Volunteer Day</li><li>
Birthday Leave</li><li>
Egg Freezing Benefits</li><li>
Employee discounts on all Kayali products</li><li>
Quarterly product gifting</li></ul> 
Kayali is committed to building diverse and inclusive teams and upholding an equal employment workplace that is free from discrimination. We hire stellar individuals regardless of their race, color, ancestry, religion, gender identity, national origin, sexual orientation, age, marital status, medical conditions, disability, or veteran status. If you need reasonable accommodations at any point in the application or interview process, please let us know.</div>

BI Engineer

<div>Job Description &ndash; 1 x Data Modeller (Erwin Data Modeler) 
Location: Abudhabi - UAE - Onsite 
Open to Relocate 
Duration: 6 months ( Extendable to One Year) 
Experience: 5 to 7 Years 
Project start date is 1st July - Immediate joiners will be preferred 
 
Role Overview 
The Data Modeller will be responsible for establishing and managing the enterprise data modelling capability for ADC using Erwin Data Modeler. The role will lead the design and delivery of authoritative data register models across conceptual, logical, and physical layers while ensuring alignment with government data standards, enterprise architecture requirements, and target platform implementations. 
 
Key Responsibilities 
Erwin Environment Setup and Governance<ul><li>
Configure and administer the Erwin Data Modeler environment for ADC.</li><li>
Establish and maintain the Erwin Mart repository for version-controlled storage of all Data Domain Model (DDM) artefacts.</li><li>
Implement DDA-approved modelling standards, naming conventions, and notation frameworks.</li><li>
Validate accessibility and operational readiness of the modelling environment for both onshore and offshore delivery teams.</li></ul>
Authoritative Data Register Definition<ul><li>
Facilitate stakeholder workshops to identify, scope, and define authoritative data registers.</li><li>
Document domain boundaries, business definitions, ownership, stewardship responsibilities, and relationships with upstream and downstream systems.</li><li>
Produce Authoritative Data Register Definition Packs for each register.</li></ul>
Conceptual, Logical and Physical Data Modelling<ul><li>
Develop conceptual data models representing high-level entities, relationships, and business rules.</li><li>
Produce supporting Data Requirements Specifications for each conceptual model.</li><li>
Develop logical data models defining entities, attributes, relationships, cardinality, and data types.</li><li>
Ensure traceability between conceptual and logical models using Erwin traceability features.</li><li>
Develop physical data models aligned to ADC&rsquo;s target architecture, including:<ul><li>
IBM DB2 Warehouse schemas.</li><li>
Databricks Delta Lake structures supporting Bronze, Silver, and Gold data pipelines.</li></ul></li><li>
Reverse engineer existing DB2 database structures where required to support reconciliation between current and target-state designs.</li></ul>
Data Traceability and Standards Alignment<ul><li>
Maintain complete traceability between approved register definitions and conceptual, logical, and physical models.</li><li>
Manage DDM ID Mapping Tables and Erwin Mart version logs.</li><li>
Align data models with the Unified Data Model (UDM) and Government Information Model (GIM).</li><li>
Maintain the GIM/UDM Alignment Register and identify gaps, conflicts, or enhancement opportunities.</li></ul>
Integration with Enterprise Data Governance<ul><li>
Collaborate with Data Catalogue Specialists to ensure data structures are accurately represented in Microsoft Purview.</li><li>
Support glossary alignment, schema consistency, metadata accuracy, and lineage requirements.</li><li>
Ensure authoritative register entities and attributes are consistently represented across modelling and catalogue platforms.</li></ul>
Review, Approval and Compliance<ul><li>
Prepare modelling artefacts for formal DDA review and approval.</li><li>
Produce Modelling Approval Packages including:<ul><li>
Erwin exports.</li><li>
DDM ID Mapping Tables.</li><li>
Data Requirements Specifications.</li><li>
GIM/UDM Alignment Register.</li></ul></li><li>
Manage review cycles, incorporate feedback, and maintain version control until formal sign-off is achieved.</li></ul>
Physical Model Controls<ul><li>
Ensure all physical models include audit columns, logging requirements, and error-handling specifications.</li><li>
Validate physical model structures against Databricks pipeline implementation requirements and enterprise data governance standards.</li></ul>
Required Skills and Experience<ul><li>
Extensive experience with Erwin Data Modeler and Erwin Mart.</li><li>
Strong background in conceptual, logical, and physical data modelling.</li><li>
Experience with enterprise data governance and metadata management frameworks.</li><li>
Knowledge of IBM DB2 Warehouse and Databricks Delta Lake architectures.</li><li>
Experience implementing data modelling standards and traceability controls.</li><li>
Strong stakeholder engagement and workshop facilitation skills.</li><li>
Understanding of government data standards, information models, and enterprise architecture practices.</li></ul>
Deliverables<ul><li>
Erwin Mart repository and modelling standards configuration.</li><li>
Authoritative Data Register Definition Packs.</li><li>
Conceptual, logical, and physical data models.</li><li>
Data Requirements Specifications.</li><li>
DDM ID Mapping Tables.</li><li>
GIM/UDM Alignment Register.</li><li>
Modelling Approval Packages and DDA sign-off artefacts.</li></ul>
0sESuOhEZS</div>

Data Modeller (Erwin Data Modeler)

Tata Consultancy Services

<div>
 
 
 Job Title
 
 &ndash; AI Engineer
 
 
 
 Company
 
 &ndash; TCS (MEA)
 
 
 
 Location
 
 &ndash; Dubai
 
 
 
 Job type
 
 &ndash; Full time
 
 
 
 
 
 
 About Us:
 
 
 
 Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world&rsquo;s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile&trade; delivery model, recognized as a benchmark of excellence in software development.
 
 
 A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world&rsquo;s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.
 
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 
 
 Key Accountabilities:
 
 
 <ul>
 <li>
 
 AI Solution Design &amp; Development:
 
 </li>
 <li>
 Design, build, and deploy AI-powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services (Speech, Vision, Language), Azure AI Search, Azure Functions, and Azure Databricks.
 </li>
 <li>
 
 LLM Integration &amp; Generative AI:
 
 </li>
 <li>
 Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT-4.1, GPT-4o, GPT-4o-mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management. Build enterprise use cases such as knowledge search, document intelligence, content summarization, call analytics, sentiment analysis, and workflow automation.
 </li>
 <li>
 
 Python Engineering &amp; Backend Development:
 
 </li>
 <li>
 Write clean, modular, and production-grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI.
 </li>
 <li>
 
 RAG &amp; Semantic Retrieval:
 
 </li>
 <li>
 Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence.
 </li>
 <li>
 
 Agentic AI Development:
 
 </li>
 <li>
 Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner.
 </li>
 <li>
 
 Model Evaluation &amp; Responsible AI:
 
 </li>
 <li>
 Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework. Ensure AI solutions comply with FAB's security, data privacy, model governance, and regulatory requirements, including controls for accuracy, hallucination, bias, latency, and resilience.
 </li>
 <li>
 
 Deployment &amp; Production Operations:
 
 </li>
 <li>
 Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques.
 </li>
 <li>
 
 Collaboration &amp; Stakeholder Engagement:
 
 </li>
 <li>
 Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions.
 </li>
 <li>
 
 Innovation &amp; Continuous Learning:
 
 </li>
 <li>
 Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy. Stay abreast of state-of-the-art developments in generative AI and agentic architectures.
 </li>
 </ul>
 
 
 
 
 
 TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory
 
 
 
 
 Azure AI Services:
 
 Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.
 
 
 
 Python Programming:
 
 Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).
 
 
 
 LLM &amp; Generative AI:
 
 Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.
 
 
 
 ML Libraries &amp; Frameworks:
 
 Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK).
 
 
 
 Vector Databases:
 
 Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.
 
 
 
 DevOps/MLOps:
 
 Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.
 
 
 
 Cloud Security &amp; Integration:
 
 Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.
 
 
 
 AI Ethics &amp; Governance:
 
 Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.
 
 
 
 
 
 
 KNOWLEDGE, SKILLS, &amp; EXPERIENCE
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred.
 
 
 
 
 Minimum Experience:
 
 
 
 
 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.
 
 
 Mandatory hands-on experience with Microsoft Azure AI Services.
 
 
 Experience working with large-scale datasets and real-time enterprise data.
 
 
 Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.
 
 
 
 
 Knowledge and Skills:
 
 
 
 
 
 Business Understanding:
 
 
 
 Strong understanding of business processes and the ability to identify opportunities for AI-driven optimization and automation across banking domains.
 
 
 
 Analytical &amp; Problem-Solving:
 
 
 
 Excellent analytical, problem-solving, debugging, and performance optimization skills with the ability to troubleshoot AI applications in production and translate complex business problems into AI solutions.
 
 
 
 Communication Skills:
 
 
 
 Strong verbal and written communication skills, capable of explaining complex AI concepts to both technical and non-technical stakeholders.
 
 
 
 Collaboration:
 
 
 
 Proven ability to work effectively in cross-functional teams, collaborating with data scientists, platform engineers, DevOps engineers, business analysts, and product teams.
 
 
 
 Responsible AI Mindset:
 
 
 
 Understanding of AI governance, model risk, data privacy, security, and compliance requirements in a regulated banking environment.
 
 
 
 Production Engineering:
 
 
 
 Ability to build, deploy, monitor, and optimize production-grade AI systems with attention to reliability, scalability, cost, and operational excellence.
 
 
 
 Adaptability &amp; Learning:
 
 
 
 Willingness to stay updated on the latest AI technologies, agentic frameworks, and cloud services, and the ability to apply them to solve evolving business challenges.
 
 
 Thank you for your interest in applying for this position with TCS. We will review your application and will get back to you if we are considering your interest in this opportunity.
 
 
 
 
 
 
 Application Deadline: 30- July -2026
 
 
 
 
 
 
 
 Privacy Note:
 
 
 
 https://www.tcs.com/connect-with-tcs/privacy-policy
 
</div>

AI Engineer

Confidential

<div>
 
 We are seeking a highly skilled Material Engineer with strong expertise in fit-out and construction projects to support the successful delivery of high-quality projects in UAE. The role is responsible for managing the selection, evaluation, approval, and compliance of all construction and finishing materials across multiple projects. The candidate will ensure that all materials meet project specifications, client requirements, and UAE regulatory standards while balancing cost efficiency, quality, and project timelines. The Material Engineer will work closely with project managers, consultants, procurement teams, and site engineers to ensure smooth material approval processes, timely procurement, and proper implementation on site. This role plays a key part in maintaining construction quality, minimizing risks, and ensuring project compliance from design stage through execution.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Review project drawings, specifications, and BOQs to identify material requirements
 </li>
 <li>
 Prepare, submit, and follow up on material submittals for consultant/client approval
 </li>
 <li>
 Ensure all materials comply with project specifications, authority regulations, and quality standards
 </li>
 <li>
 Maintain a structured material approval register and tracking system
 </li>
 <li>
 Evaluate alternative materials and propose value engineering solutions where applicable
 </li>
 <li>
 Assess material samples for quality, durability, performance, and cost efficiency
 </li>
 <li>
 Coordinate technical clarifications between suppliers, consultants, and project teams
 </li>
 <li>
 Work closely with procurement teams to ensure timely sourcing of approved materials
 </li>
 <li>
 Coordinate with suppliers and vendors for technical data, samples, and certifications
 </li>
 <li>
 Track material lead times and ensure alignment with project schedules
 </li>
 <li>
 Provide technical support to site teams regarding material usage and installation methods
 </li>
 <li>
 Resolve material-related issues during construction to avoid delays or rework
 </li>
 <li>
 Ensure correct material implementation as per approved submittals
 </li>
 <li>
 Maintain accurate records of all material approvals, submittals, and correspondence
 </li>
 <li>
 Ensure all materials meet UAE standards, project requirements, and safety regulations
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 Support audits and quality inspections when required
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 <li>
 Bachelor&rsquo;s degree in Civil Engineering, Architecture, or related field
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 <li>
 Proven experience as a Material Engineer in fit-out and/or construction projects
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 <li>
 Strong knowledge of construction materials, specifications, and approval processes
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 <li>
 Experience in UAE construction industry preferred
 </li>
 <li>
 Good communication and coordination skills
 </li>
 <li>
 Ability to work under pressure and manage multiple projects
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Civil Engineering, Architecture, or related field
 </li>
 <li>
 8-10 years of experience in a Material Engineer in fit-out and/or construction projects
 </li>
 <li>
 Strong knowledge of construction materials, specifications, and approval processes
 </li>
 <li>
 Experience in UAE construction industry preferred
 </li>
 <li>
 Good communication and coordination skills
 </li>
 <li>
 Ability to work under pressure and manage multiple projects
 </li>
 </ul>
</div>

Material Engineer

Pools International

Job DescriptionA leading GRP swimming pool company seek an experienced and efficient site engineer for our engineering / construction department.As a site engineer, you will monitor diversified aspects of construction project management. This will include planning, coordination and supervision of on-site activities. You will ensure all aspects of the project align with engineering and design specifications, industry standards and construction regulations. You will also foster effective communication by liaising with contractors, subcontractors and other project stakeholders.We offer competitive remuneration packages at par with industry standards alongside a fast-paced, collaborative work culture. Since we foster an inclusive workforce, candidates from all backgrounds are encouraged to apply for this position.Objectives of this role<ul><li>Supervising and managing company projects from start to finish, ensuring adherence to project plans and specifications.</li><li>Reporting project updates, milestones and potential risks to the project manager and key stakeholders.</li><li>Analysing and interpreting engineering drawings, survey reports and other technical documentation to guide the construction process.</li><li>Planning and overseeing allocating resources, materials and equipment to optimise project efficiency.</li><li>Monitoring project costs, identifying cost-saving opportunities and adhering to budget constraints.</li><li>Providing technical guidance and expertise to resolve construction-related challenges.</li></ul>Your tasks<ul><li>Oversee and manage all activities at the site, ensuring adherence to project specifications, codes and safety regulations.</li><li>Conduct regular site inspections to monitor progress, identify potential issues and ensure compliance with engineering and design requirements.</li><li>Collaborate closely with project managers, architects and subcontractors to ensure timely project completion.</li><li>Analyze and interpret engineering plans, aerial photography, blueprints, topographical &amp; geologic data and technical drawings to plan and execute construction activities.</li><li>Coordinate the procurement and delivery of materials, ensuring their compliance with industry standards.</li><li>Identifying potential risks and implementing preventive measures to minimize project delays, cost overruns and safety hazards.</li><li>Maintain accurate project documentation, including progress reports, site diaries, change orders and quality control measures.</li></ul>Required skills and qualifications<ul><li>A bachelor&rsquo;s degree in Civil / MEP engineering from an accredited university or college.</li><li>4-5 years of experience as a site engineer, Civil / MEP engineer or an equivalent role.</li><li>Swimming pool work experience is an advantage.</li><li>Demonstrated proficiency in managing and supervising construction projects.</li><li>Experience with Microsoft Office Suite, AutoCAD and other softwares.</li><li>Ability to manage multiple construction projects at various stages of their lifecycle.</li><li>Strong knowledge of construction methods, materials and regulations.</li><li>Competent in assessing, interpreting and presenting survey reports and other critical data for stakeholders and shareholders.</li><li>Excellent project management and organisational skills.</li><li>Strong problem-solving and decision-making abilities with effective communication.</li><li>Ability to work effectively in a team and coordinate with multiple stakeholders.</li><li>Attention to detail and a focus on delivering high-quality results.</li><li>Willing to join immediate.</li></ul>Preferred skills and qualifications<ul><li>Excellent interpersonal, leadership and management skills.</li><li>Knowledge of sustainable construction practices.</li><li>Understanding of budgeting and cost control.</li><li>Must need a driving license.</li></ul>Work Location: In person

Site Engineer / Foreman

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