graphic designer

civil engineer

planning engineer

project engineer

business analyst

data architect

The Glove

<div>
 
 
 Role : Data Lakehouse Architect
 
 
 
 
 Location:
 
 UAE (Dubai preferred) - On-site
 
 
 
 Experience:
 
 11 years - 16 years
 
 
 
 Notice period :
 
 immediate to 15 days max.
 
 
 
 Note: Candidate should be from the Retail or Ecommerce domain only
 
 
 
 
 
 
 
 ROLE OVERVIEW
 
 
 
 We are looking for a hands-on
 
 Lead Data Engineer
 
 with 11+ years experience who has built and operated production-grade data lakehouse platforms.
 
 
 This person will work directly under the Data Lakehouse Architect and own the end-to-end engineering execution across ingestion, transformation, orchestration, governance, and consumption layers. This is a technical delivery role requiring deep engineering skills and the ability to work across all layers of the lakehouse.
 
 
 
 
 
 
 KEY RESPONSIBILITIES
 
 
 <ul>
 <li>
 Build and operate end-to-end ingestion pipelines from 20+ heterogeneous source systems including Oracle Retail, WMS, TMS, Loyalty platforms, and third-party APIs into the Bronze layer
 </li>
 <li>
 Implement CDC pipelines for real-time and near-real-time data capture across relational and NoSQL sources
 </li>
 <li>
 Design and build Silver and Gold transformation layers including data cleansing, enrichment, SCD Type 1 and 2, and complex business rule application
 </li>
 <li>
 Develop and maintain orchestration workflows with automated retry, failure alerting, and SLA tracking
 </li>
 <li>
 Implement data quality checks, validation rules, and reprocessing/backfill capabilities
 </li>
 <li>
 Enforce security policies, PII masking, row-level and column-level access control as defined by the Architect
 </li>
 <li>
 Enable consumption layers for Tableau, direct SQL users, and downstream API integrations
 </li>
 <li>
 Support historical data migration from legacy cloud data warehouse into the lakehouse
 </li>
 <li>
 Maintain pipeline documentation, source-to-target mappings, and data dictionaries
 </li>
 <li>
 Build clean, well-structured data pipelines that support AI/ML feature engineering and model training workflows
 </li>
 </ul>
 
 
 
 
 
 REQUIRED SKILLS AND EXPERIENCE
 
 
 <ul>
 <li>
 12+ years in data engineering with hands-on experience across ingestion, transformation, orchestration, and governance layers in production lakehouse environments
 </li>
 <li>
 Proficient in Python and PySpark for pipeline development and custom connector building
 </li>
 <li>
 Hands-on experience with cloud data services (e.g. S3/Blob Storage, Glue, DMS, Kinesis/Event Hubs, EMR or equivalent)
 </li>
 <li>
 Strong CDC implementation experience using DMS, Debezium, or equivalent across Oracle, RDS, and NoSQL sources
 </li>
 <li>
 Experienced with Delta Lake/Apache Iceberg ACID transactions, merge/upsert operations, and partition management at scale
 </li>
 <li>
 Strong hands-on experience with dbt for SQL-based transformation layers
 </li>
 <li>
 Proficient with orchestration tools such as Apache Airflow (MWAA), Dagster, or Step Functions
 </li>
 <li>
 Experienced with data quality frameworks such as Great Expectations, Deequ, or dbt tests
 </li>
 <li>
 Hands-on with security implementation: IAM policies, PII masking, column-level and row-level access control
 </li>
 <li>
 Strong SQL skills and dimensional modeling (star schema, snowflake schema) for BI consumption layers
 </li>
 <li>
 Retail or e-commerce domain experience (Oracle Retail, Magento, Shopify, WMS, TMS) is a strong advantage
 </li>
 <li>
 Familiarity with AI/ML pipeline requirements including feature store design, data preparation for model training, and vector database integration
 </li>
 </ul>
 
 
 
 
 
 PREFERRED / NICE-TO-HAVE PLATFORMS
 
 
 <ul>
 <li>
 AWS (Lake Formation, Glue, Redshift, EMR, SageMaker)
 </li>
 <li>
 Databricks
 </li>
 <li>
 Snowflake
 </li>
 <li>
 Microsoft Fabric
 </li>
 <li>
 Google BigQuery
 </li>
 <li>
 Dataiku
 </li>
 <li>
 Apache Iceberg / Hudi
 </li>
 </ul>
 
 
 
 
 
 EDUCATION
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science, Information Systems, or a related field
 </li>
 <li>
 Cloud Data Analytics or Solutions Architect certification from a major cloud provider (AWS, Azure, or GCP) is a strong advantage
 </li>
 <li>
 Databricks Certified Data Engineer or Snowflake SnowPro certifications are a plus
 </li>
 </ul>
 
 
 
 
 
 Interested candidates share their resume at uma.jangra@glovetalent.com !!
 
 
</div>

Data Lakehouse Architect

Vitage Systems Pvt Ltd

Role: Pega CDH &ndash; Lead System ArchitectClient Location: Dubai● 7+years of experience in Pega and 3-4 years of experience in Pega CDH● Pega CSSA Certification and Pega Decisioning Consultant● Experience in Pega CDH 8.X or higher versions and NBAD framework.● Hands-on experience with Pega CDH components like ADM, DSM, Value Finder, Customer Profiler, etc.● Proficiency in SQL, JSON, real-time decisioning, and object-oriented programming principles.● Design and configure core decisioning logic using Pega CDH, including rules, propositions, treatments, and decision data flows.● Manage the end-to-end delivery of Pega CDH solutions in Agile environments.● Good understanding and experience in Client Server applications, Digital applications, and Business Functions● Designing and implementing REST API, Kafka and FTP based integrations● Strong analytical skills with the ability to summarize data into actionable insights.● Excellent communication skills to interact with both technical and non-technical stakeholders.● Designing in alignment with Clients Business objectiveGood to have skills:<ul><li>Pega Lead system architect.</li><li>Knowledge in externalisation of Cassandra , KAFKA, Elastic search</li><li>Familiarity with DevOps practices such as CI/CD pipelines for deployment automation.</li><li>Knowledge of emerging trends in marketing automation and hyper-personalization.</li></ul>Pay: AED18,000.00 - AED20,000.00 per monthApplication Question(s):<ul><li>How many years of experience do you have in Pega?</li><li>How much experience do you have in Pega CDH?</li><li>Have you worked on NBAD framework?</li><li>Do you have Pega CSSA or LSA certification?</li><li>Have you worked on ADM or Decision Strategies?</li><li>Do you have experience with REST APIs or Kafka integration?</li><li>Have you worked on real-time decisioning projects?</li><li>Which Pega CDH version have you worked on?</li><li>Are you comfortable working with Dubai clients?</li><li>What is your current CTC, expected CTC, and notice period?</li></ul>Work Location: In person

Pega CDH – Lead System Architect

Dyson

<div>
 
 About Us
 
 
 
 At Dyson, we&rsquo;re driven by a relentless pursuit of innovation&mdash;pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson&rsquo;s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.
 
 
 You&rsquo;ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.
 
 
 
 About The Role
 
 
 
 We are looking for a specialized Lead Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.
 </li>
 <li>
 Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.
 </li>
 <li>
 Quality Assurance &amp; Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.
 </li>
 <li>
 Tooling &amp; Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.
 </li>
 <li>
 Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.
 </li>
 <li>
 Set up and maintain robust data preparation infrastructure&mdash;optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.
 </li>
 <li>
 Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You&rsquo;ll help transform raw data into actionable insight, supporting both research and deployment.
 </li>
 <li>
 Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.
 
 
 
 </li>
 </ul>
 
 About you
 
 
 
 <ul>
 <li>
 At least 8+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.
 </li>
 <li>
 Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).
 </li>
 <li>
 Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).
 </li>
 <li>
 Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).
 </li>
 <li>
 Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.
 </li>
 <li>
 Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.
 </li>
 <li>
 Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.
 </li>
 <li>
 Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).
 </li>
 <li>
 Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).
 </li>
 <li>
 Strong background in feature engineering, data analysis, and data visualization&mdash;comfortable using tools like Jupyter, Tableau, or Power BI.
 </li>
 <li>
 Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.
 </li>
 <li>
 Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.
 </li>
 <li>
 Bachelor&rsquo;s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.
 
 
 
 </li>
 </ul>
 Dyson is an equal opportunity employer. We know that great minds don&rsquo;t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
</div>

Lead Data Intelligence Machine Learning Engineer

Rackspace Technology

<div>
 Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We&rsquo;ve evolved Fanatical Support to encompass the entire customer journey &mdash; providing Fanatical Experience&trade; from first consultation to daily operations. Our passionate experts combine the power of proactive, always-on service and expertise with best-in-class tools and automation to deliver technology when and how our customers need it.
 
 
 As a Data Modeler, you will design and deliver implementation-ready
 
 logical and physical data models
 
 within
 
 Azure Databricks (Delta Lake)
 
 following
 
 Medallion Architecture (Bronze, Silver, Gold)
 
 .
 
 
 The role ensures Data Engineers can immediately begin development with clear schema definitions, SQL structures, and zero ambiguity.
 
 
 
 Key Responsibilities
 
 
 
 
 
 Data Modelling &amp; Design
 
 
 
 
 <ul>
 <li>
 Develop Conceptual, Logical, and Physical Data Models.
 </li>
 <li>
 Define schemas, entities, attributes, relationships, keys, constraints, and data types.
 </li>
 <li>
 Provide DDL-ready SQL definitions for implementation.
 </li>
 <li>
 Clearly define fact table grain and dimensional structures.
 
 
 </li>
 </ul>
 
 
 Azure Databricks &ndash; Medallion Modelling
 
 
 
 
 <ul>
 <li>
 Design structured models across:
 </li>
 <li>
 Bronze Layer &ndash; Raw ingestion, schema control.
 </li>
 <li>
 Silver Layer &ndash; Cleansed, conformed, standardized data.
 </li>
 <li>
 Gold Layer &ndash; Business-ready dimensional models.
 </li>
 <li>
 Define transformation logic across layers (Bronze &rarr; Silver &rarr; Gold).
 </li>
 <li>
 Incorporate Delta Lake best practices (partitioning, performance, scalability).
 
 
 </li>
 </ul>
 
 
 Advanced Modelling Techniques
 
 
 
 .
 
 
 
 
 Requires Strong Hands-on Expertise In
 
 
 
 <ul>
 <li>
 3rd Normal Form (3NF)
 </li>
 <li>
 Star Schema
 </li>
 <li>
 Snowflake Schema
 </li>
 <li>
 Data Vault (Hubs, Links, Satellites)
 
 
 </li>
 </ul>
 
 Must Clearly Define
 
 
 
 <ul>
 <li>
 Fact grain
 </li>
 <li>
 Surrogate key strategy
 </li>
 <li>
 Slowly Changing Dimensions (Type 1 &amp; 2)
 </li>
 <li>
 Conformed dimensions
 </li>
 <li>
 Aggregation strategy
 
 
 </li>
 </ul>
 
 
 Engineering &amp; Governance Alignment
 
 
 
 
 <ul>
 <li>
 Ensure models are build-ready for Data Engineering teams.
 </li>
 <li>
 Review implementation alignment with design.
 </li>
 <li>
 Maintain ER diagrams, data dictionary, mapping documents.
 </li>
 <li>
 Enforce enterprise naming standards and modelling best practices.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 5+ years of hands-on Data Modelling experience.
 </li>
 <li>
 Strong SQL (DDL, partitioning, performance concepts).
 </li>
 <li>
 Proven experience in Azure Databricks and Delta Lake environments.
 </li>
 <li>
 Deep understanding of Medallion Architecture.
 </li>
 <li>
 Experience in enterprise Data Warehouse or Modern Data Platform projects.
 </li>
 <li>
 Proficiency with data modelling tools (ERwin, ER Studio,
 </li>
 <li>
 PowerDesigner, Lucidchart, or similar).
 
 
 </li>
 </ul>
 
 About Rackspace Technology
 
 
 
 We are the multicloud solutions experts. We combine our expertise with the world&rsquo;s leading technologies &mdash; across applications, data and security &mdash; to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.
 
 
 
 More on Rackspace Technology
 
 
 
 Though we&rsquo;re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
</div>

Data Modeler

GSSTech Group

<div>We are looking for a highly skilled Data Engineer with strong expertise in PySpark and Informatica Platform Engineering to support enterprise-scale Digital Products and Digital Onboarding initiatives.
The ideal candidate should have strong experience in enterprise data engineering, big data ecosystems, data architecture, and modern data management practices within large and complex environments, preferably in banking or financial services. 
Requirements 
 
Key Responsibilities<ul><li>
Design and develop scalable enterprise data engineering solutions using PySpark and Informatica platforms</li><li>
Build and model Raw Data Vault structures with strong understanding of:</li><li><ul><li>
Source system data structures</li><li>
Data retention policies</li><li>
Data partitioning strategies</li></ul></li><li>
Drive data reusability and reduce data duplication while optimizing performance</li><li>
Define and implement enterprise data architecture standards and best practices</li><li>
Create data exchange standards to support reusable and decoupled architectures</li><li>
Define standards for data archival, retention, and purging</li><li>
Identify and document critical data elements across enterprise source systems</li><li>
Collaborate with data engineers, architects, and source system SMEs to establish data engineering principles and governance standards</li><li>
Support large-scale data transformation and analytics initiatives</li><li>
Contribute to CI/CD-enabled data engineering and deployment environments</li><li>
Ensure compliance with enterprise data quality, governance, and security standards</li></ul>
Required Skills &amp; Experience<ul><li>
Strong hands-on experience in:</li><li><ul><li>
PySpark</li><li>
Informatica Platform Engineering</li><li>
Enterprise Data Engineering</li><li>
Big Data Ecosystems</li></ul></li><li>
Strong expertise in:</li><li><ul><li>
Data Architecture</li><li>
Data Strategy &amp; Roadmaps</li><li>
Enterprise Data Management</li><li>
Data Warehousing &amp; Analytics Solutions</li></ul></li><li>
Strong understanding of:</li><li><ul><li>
Dimensional Modeling</li><li>
Star &amp; Snowflake Schemas</li><li>
Slowly Changing Dimensions (SCD)</li><li>
Role-playing Dimensions</li><li>
Dimensional Hierarchies</li><li>
Data Classification</li></ul></li><li>
Experience transforming traditional Data Warehouse environments into Big Data-based architectures</li><li>
Expertise in:</li><li><ul><li>
Data Quality</li><li>
Data Profiling</li><li>
Data Governance</li><li>
Data Security</li><li>
Metadata Management</li><li>
Data Archival</li></ul></li><li>
Experience with cloud-native principles, architectures, and deployments</li><li>
Strong exposure to Continuous Integration (CI) and Continuous Deployment (CD) environments</li><li>
Strong analytical, troubleshooting, and problem-solving capabilities</li></ul>
Preferred Experience<ul><li>
Banking or financial services domain experience is highly preferred</li><li>
Experience working within enterprise-scale digital transformation programs</li><li>
Exposure to modern analytics and enterprise data platforms</li></ul>
Education
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Systems, Information Technology, Engineering, or related field
Preferred Candidate Profile<ul><li>
Ability to work in fast-paced and evolving environments</li><li>
Strong stakeholder collaboration and communication skills</li><li>
Experience handling multiple priorities and enterprise-scale projects</li><li>
Strong ownership mindset and attention to detail</li></ul></div>

Data Engineer - PySpark & Informatica

<div>Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We&rsquo;ve evolved Fanatical Support to encompass the entire customer journey &mdash; providing Fanatical Experience&trade; from first consultation to daily operations. Our passionate experts combine the power of proactive, always-on service and expertise with best-in-class tools and automation to deliver technology when and how our customers need it.
As a Data Modeler, you will design and deliver implementation-ready logical and physical data models within Azure Databricks (Delta Lake) following Medallion Architecture (Bronze, Silver, Gold) .
The role ensures Data Engineers can immediately begin development with clear schema definitions, SQL structures, and zero ambiguity.
Key Responsibilities
Data Modelling &amp; Design
&bull; Develop Conceptual, Logical, and Physical Data Models.
&bull; Define schemas, entities, attributes, relationships, keys, constraints, and data types.
&bull; Provide DDL-ready SQL definitions for implementation.
&bull; Clearly define fact table grain and dimensional structures.
Azure Databricks &ndash; Medallion Modelling
&bull; Design structured models across:
o Bronze Layer &ndash; Raw ingestion, schema control.
o Silver Layer &ndash; Cleansed, conformed, standardized data.
o Gold Layer &ndash; Business-ready dimensional models.
&bull; Define transformation logic across layers (Bronze Silver Gold).
&bull; Incorporate Delta Lake best practices (partitioning, performance, scalability).
Advanced Modelling Techniques .
Requires strong hands-on expertise in:
&bull; 3rd Normal Form (3NF)
&bull; Star Schema
&bull; Snowflake Schema
&bull; Data Vault (Hubs, Links, Satellites)
Must clearly define:
&bull; Fact grain
&bull; Surrogate key strategy
&bull; Slowly Changing Dimensions (Type 1 &amp; 2)
&bull; Conformed dimensions
&bull; Aggregation strategy
Engineering &amp; Governance Alignment
&bull; Ensure models are build-ready for Data Engineering teams.
&bull; Review implementation alignment with design.
&bull; Maintain ER diagrams, data dictionary, mapping documents.
&bull; Enforce enterprise naming standards and modelling best practices.
Required Skills &amp; Experience
&bull; 5+ years of hands-on Data Modelling experience.
&bull; Strong SQL (DDL, partitioning, performance concepts).
&bull; Proven experience in Azure Databricks and Delta Lake environments.
&bull; Deep understanding of Medallion Architecture.
&bull; Experience in enterprise Data Warehouse or Modern Data Platform projects.
&bull; Proficiency with data modelling tools (ERwin, ER Studio,
&bull; PowerDesigner, Lucidchart, or similar). 
About Rackspace Technology
We are the multicloud solutions experts. We combine our expertise with the world&rsquo;s leading technologies &mdash; across applications, data and security &mdash; to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.
More on Rackspace Technology
Though we&rsquo;re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.</div>

AMroute LLC

<div>
 Position: 1 Duration: 12 months Location: Dubai Address:
 
 
 3, Al Rigga road Al Muraqqabat, Deira, Dubai Level 7 Working Hours/Time Zone: 8 hrs/day, UAE time (following the UAE labour law) Onsite/Remote: Onsite interview process: All profiles will go through online test, only the candidates who cleared the test will go through the 2 rounds of interview - 1- Internal Technical discussion, 2- Client Technical discussion. Bill Rate: USD 20-22/hr -
 
 
 This will be the only rate accepted Top 3 requirements: Strictly follow the JD shared, Worked as a data modeller (must have - more than 8+ experience as data modeller), clear understanding on the data modelling concepts, has experience on implementing the data modelling in Lakehouse projects.
 
 
 Job Description: 8+ yrs of Data Modelling experience.
 
 
 Data Modeler - Azure Databricks (Medallion Architecture)
 
 
 Role Purpose
 
 
 Design and deliver implementation-ready logical and physical data models within Azure Databricks (Delta Lake) following Medallion Architecture (Bronze, Silver, Gold).
 
 
 The role ensures Data Engineers can immediately begin development with clear schema definitions, SQL structures, and zero ambiguity.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Data Modelling &amp; Design
 </li>
 <li>
 Develop Conceptual, Logical, and Physical Data Models.
 </li>
 <li>
 Define schemas, entities, attributes, relationships, keys, constraints, and data types.
 </li>
 <li>
 Provide DDL-ready SQL definitions for implementation.
 </li>
 <li>
 Clearly define fact table grain and dimensional structures.
 </li>
 <li>
 Azure Databricks - Medallion Modelling
 </li>
 <li>
 Design structured models across:
 
 
 </li>
 </ul>
 &cir; Bronze Layer - Raw ingestion, schema control.
 
 
 &cir; Silver Layer - Cleansed, conformed, standardized data.
 
 
 &cir; Gold Layer - Business-ready dimensional models.
 
 
 Data Modeler - Azure Databricks (Medallion Architecture)
 
 
 <ul>
 <li>
 Define transformation logic across layers (Bronze &rarr; Silver &rarr; Gold).
 </li>
 <li>
 Incorporate Delta Lake best practices (partitioning, performance, scalability).
 </li>
 <li>
 Advanced Modelling Techniques
 
 
 </li>
 </ul>
 Strong hands-on expertise in:
 
 
 <ul>
 <li>
 3rd Normal Form (3NF)
 </li>
 <li>
 Star Schema
 </li>
 <li>
 Snowflake Schema
 </li>
 <li>
 Data Vault (Hubs, Links, Satellites)
 
 
 </li>
 </ul>
 Must clearly define:
 
 
 <ul>
 <li>
 Fact grain
 </li>
 <li>
 Surrogate key strategy
 </li>
 <li>
 Slowly Changing Dimensions (Type 1 &amp; 2)
 </li>
 <li>
 Conformed dimensions
 </li>
 <li>
 Aggregation strategy
 </li>
 <li>
 Engineering &amp; Governance Alignment
 </li>
 <li>
 Ensure models are build-ready for Data Engineering teams.
 </li>
 <li>
 Review implementation alignment with design.
 </li>
 <li>
 Maintain ER diagrams, data dictionary, mapping documents.
 </li>
 <li>
 Enforce enterprise naming standards and modelling best practices.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 8+ years of hands-on Data Modelling experience.
 </li>
 <li>
 Strong SQL (DDL, partitioning, performance concepts).
 </li>
 <li>
 Proven experience in Azure Databricks and Delta Lake environments.
 </li>
 <li>
 Deep understanding of Medallion Architecture.
 </li>
 <li>
 Experience in enterprise Data Warehouse or Modern Data Platform projects.
 </li>
 <li>
 Proficiency with data modelling tools (ERwin, ER Studio, PowerDesigner, Lucidchart, or similar).
 </li>
 </ul>
</div>

Data Modeler – Azure Databricks (Medallion Architecture) - RAXJP00002194 - Dubai

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Data Modeler – Azure Databricks (Medallion Architecture) - RAXJP00002194 - Dubai