68 Data Architects jobs in Dubai

Lead Data Modeling and Analytics Specialist

This role will oversee the strategic planning, development, and management of advanced analytics technologies to enhance customer engagement and satisfaction.

• Develop and implement a comprehensive data modeling strategy to improve customer experience.
• Implement and support sophisticated ETL tools such as DataStage and Talend.
• Deploy solutions on platforms like Data Warehouse, Cloudera, and Big Data using expertise in NLP tools and model training.
• Ensure seamless integration with enterprise systems and applications.
• Drive technology adoption and provide training for effective utilization.
• Design and implement AI-powered solutions to streamline business processes and deliver data-driven insights.
• Collaborate to implement intelligent automation across various business functions.
• Lead cross-functional teams to deliver projects on time and within budget.
• Collaborate to align compliance technology initiatives with organizational priorities.
• Presentation of project updates and progress reports to senior leadership.

Minimum bachelor's degree in IT Engineering with a statistics background.

12-16 years of experience in leading Advanced Analytics roles in financial industries.

• Proven experience in managing large-scale analytical projects and teams.
• Strong analytics strategy development and implementation background.
• Hands-on experience with leading-edge technologies and deployment of use cases on cloud platforms.
• Deep understanding of model governance and open analytics.
• Excellent communication and stakeholder management skills.

Position Overview

The Data Architect is responsible for designing, implementing, and maintaining an organization's data architecture and strategy, ensuring that data is collected, stored, and processed efficiently and securely to support business intelligence, data analytics, and machine learning operations (MLOps) practices.

Key Responsibilities

• Designing Data Architecture: Plan and implement a robust, scalable data architecture that integrates data from various sources and supports diverse analytical needs, while optimising costs and meeting business requirements.
• Implementing Data Engineering Pipelines: Design and develop data pipelines for data extraction, transformation, and loading (ETL) processes, ensuring data quality and consistency.
• Enabling Data Intelligence and Analytics: Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives.
• Supporting MLOps Practices: Collaborate with data scientists and machine learning engineers to design and implement data infrastructure and processes that support machine learning model development, deployment, and maintenance.
• Ensuring Data Security and Compliance: Implement security measures, policies, and procedures to safeguard data privacy and comply with relevant regulations.
• Data Governance and Management: Establish and enforce data governance policies and standards to ensure data quality, integrity, and accessibility.
• Collaborating with Cross-Functional Teams: Work closely with data engineers, data scientists, business analysts, and other stakeholders to understand data requirements and translate them into technical solutions.
• Staying Abreast of Technological Advancements: Keep up-to-date with emerging technologies and trends in data architecture, data engineering, and MLOps to identify opportunities for improvement and innovation.
• Optimising Data Performance: Monitor and analyze data processing performance, identify bottlenecks, and implement optimisations to enhance efficiency and scalability.
• Documentation and Knowledge Sharing: Create and maintain comprehensive documentation of data architecture, models, and processing workflows.

Technical Requirements

• Extensive experience in data architecture design and implementation.
• Hands-on experience with Amazon Redshift for data warehousing, query optimization, and integration with AWS analytics services.
• Strong knowledge of data engineering principles and practices.
• Expertise in data warehousing, data modelling, and data integration.
• Experience in MLOps and machine learning pipelines.
• Proficiency in SQL and data manipulation languages.
• Experience with big data platforms (including PowerBI, DBT, Databricks, MySQL, Postgres, Clickhouse, Kafka, Redis etc) and cloud-based infrastructure on AWS.

Education & Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Preferred certifications (optional):
• AWS Machine Learning Ops Engineer

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries: Software Development, Data Infrastructure and Analytics, and IT System Custom Software Development

Responsible for designing, implementing, and managing the organization's data architecture to ensure data availability, accuracy, security, and scalability.

• Design and optimize data models, databases, and pipelines.
• Define and enforce data governance, standards, and best practices.
• Collaborate with business and technical teams to translate requirements into scalable data solutions.
• Ensure data quality, integrity, and security across systems.
• Evaluate and implement data tools, platforms, and cloud solutions (AWS, Azure, GCP).

• Strong knowledge of data modeling, ETL/ELT, and data warehousing.
• Proficiency in SQL, NoSQL, and big data technologies.
• Experience with cloud platforms and modern data architectures (e.g., lakehouse, streaming).
• Understanding of data governance, compliance, and security.

• Not Applicable

• Contract

• Engineering and Information Technology

• IT Services and IT Consulting

Senior Data Scientist Position

This role is ideal for a highly skilled data scientist with expertise in designing and implementing production-ready algorithms and models to manage risk and drive business growth.

• Develop predictive and forecasting models for risk management and business growth.
• Full model cycle from experimentation to deployment, including model calibration and post-modeling adjustments.
• Regional and International Asset Risk Monitoring.
• Calculate RV Provisions, identify hand-backs, and quantify feature impact.
• Conduct statistical and quantitative analyses to identify potential risks.
• Design and develop risk measures, methodologies, and models.
• Define pull-forward or backward strategy to optimize trade cycles.
• Quantify feature importance in Time-to-fail and Mileage-to-fail.

• 5+ years of experience in financial services, specializing in data analytics and business intelligence.
• Strong knowledge of statistics, Python, and SQL for data modeling, automation, and reporting.
• Proven track record in delivery of analytics use cases such as credit risk modeling, fraud detection, customer segmentation, and compliance reporting.
• 5+ years of hands-on experience in Data Science (Machine Learning, NLP, Neural Nets, Time-Series Forecasting, etc.). Supervised and un-supervised learning methods for inference on data patterns.

You will be working under the guidance of an experienced Head of Data Science & Asset Risk.

Data Architect

We are seeking a skilled Data Architect to join our team. As a Data Architect, you will play a critical role in designing and maintaining our data architectures.

This includes working with databases and processing systems to ensure efficient data extraction and transformation.

You will be responsible for designing and building data pipelines, acquiring and integrating new data sources, and optimizing data quality and reliability.

• Degree qualified in data science or related field
• Extensive experience with SQL, Python, and R programming languages
• Experience with Airflow, Spark, Hadoop, and PostgreSQL

We offer flexible and collaborative solutions to any organization that requires IT experts. Our agile approach focuses on essential skills and abilities. We encourage applications from a diverse array of backgrounds.

Quantitative Researcher Job Description

• We are seeking a skilled Quantitative Researcher to work with us in Dubai. This role involves developing and implementing quantitative models to support our business strategies.

The successful candidate will be responsible for analyzing market data, conducting statistical and scenario-based modeling, and monitoring power markets and pricing trends.

• Develop and implement advanced mathematical models to inform our trading and risk management decisions.
• Analyze large datasets to identify trends and patterns that can help optimize our business performance.
• Collaborate with our engineering and operations teams to integrate models into our decision-making processes.

• Strong proficiency in Python programming language is essential, with experience using libraries for data analysis, modeling, and visualization.
• A solid understanding of statistical modeling, optimization techniques, and data analysis is required.
• Experience working with time series or market data, preferably in energy or commodities markets, is highly valued.

• Competitive salary and equity sign-on bonus.
• Biannual bonus scheme that rewards your hard work.
• Fully expensed technology to match your needs.
• Paid annual leave and a range of benefits.

We are a leading company in the energy industry, and we are looking for talented individuals to join our team. If you have 1+ years of experience in quantitative modeling, data analysis, or a related field, we would love to hear from you.

Education

• Master or Bachelor’s degree in computer science, information systems management or related field.
• Solution and Architecture certifications such as TOGAF or other.

• More than 5+ years of experience in information technology, with 2+ years spent in data architecture or technology solutions definitions and implementations.
• Extensive experience in banking and financial services domain

• Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions
• Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security
• Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification
• Experiences in cloud native principals, designs and deployments.
• Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments
• Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival
• Define workload migration strategies using appropriate tools
• Drive delivery in a matrixed environment working with various internal IT partners
• Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously
• Must be able to work independently and have skills in planning, strategy, estimation, scheduling
• Strong problem solving, influencing, communication, and presentation skills, self-starter
• Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.)
• Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenkins)
• Exposure to BI tools and reporting software (e.g. MS PowerBI and Tableau)

Job Description

Role Summary

As a Senior Analytical Engineer, you will be a core member of the data architect team, responsible for transforming raw data into high-quality, actionable insights. Your mission is to build, own, and maintain the data products that power our analytics, reporting, and business decisions. You will work across the entire data lifecycle, from data ingestion to delivering final insights, ensuring data quality and governance are central to everything you build.

This role requires a unique blend of technical expertise in data modeling, data pipelines, data quality, a strong business acumen to understand complex problems, and exceptional communication skills to collaborate with diverse teams. You will act as the key link between our data science, engineering, product, and the business, driving value by making data trustworthy and accessible.

What's On Your Plate?

As an Analytical Engineer and Data Architect, you will be responsible for :

1. Data Product Development & Ownership

Build and Maintain : Design, build, and maintain enterprise data warehouses and analytical data marts.

Translate Needs : Work closely with data scientists, product managers, and business teams to understand their problems and translate complex business requirements into robust data models and data products.

End-to-End Responsibility : Take full ownership of data products from concept to production, ensuring they are scalable, reliable, and well-documented.

2. Data Quality & Governance

Enhance Data Quality : Implement and enforce data quality and governance standards throughout the data pipeline, moving checks and enrichment upstream.

Root Cause Analysis : Proactively identify data quality and governance shortfalls, perform root cause analysis, and implement solutions with monitoring mechanisms.

3. Cross-Functional Collaboration

Collaborate : Partner with data engineers to ensure smooth data ingestion from source systems and with backend engineers to define and implement data contracts.

Consult : Serve as a subject matter expert for analytical and business teams, guiding them on best practices for data consumption and model design.

4. Data Pipeline & Modeling Expertise

Pipeline Management : Design and optimize data pipelines to support data transformation, data structures, metadata, and dependency management.

Modern Modeling : Apply a variety of data modeling techniques, including modern methods, to build efficient and flexible data solutions.

Qualifications

What Did We Order?

Experience : 5+ years of experience in data management, with a strong focus on analytical engineering.

Technical Skills : Advanced SQL knowledge and experience with relational and non-relational databases. Proficient in building and optimizing data pipelines and analytical data models.

Data Modeling : Solid experience with various data modeling techniques, including modern methodologies.

Center of Excellence : Build best practices and processes supporting data transformation, data structures, metadata, dependency, and workload management.

Problem-Solving : A strong problem-solver with a "figure it out" growth mindset and a "keep it simple" approach.

Collaboration : Proven ability to work effectively with cross-functional teams in a dynamic environment. Excellent collaborator and communicator who can translate business needs into technical solutions.

Ownership : A strong sense of ownership and accountability for data products and their impact.

Education : Bachelor's degree in engineering, computer science, technology, or a similar field.

Job Title: Visionary Data Architect

Department: Enterprise Data and AI

Reports To: Senior Technology Executive

We are seeking a highly experienced Senior Data Architect to lead the design and implementation of enterprise-wide data architectures driving digital and AI transformation initiatives.

This role is based in Dubai, working with C-suite leaders and technical teams to architect scalable, secure and business-aligned data ecosystems across industries including government, financial services, energy and retail.

Key Responsibilities:

• Lead Data Architecture Strategy :
• Define enterprise and solution-level data architecture strategies.
• Design modern data platforms (data lakes, warehouses, lakehouses) on cloud (Azure, AWS, GCP).
• Champion data mesh, data fabric or other advanced architectural patterns.
• Engage with Business & Technology Stakeholders :
• Collaborate with business units to understand their data needs and translate them into technical solutions.
• Support data governance, security, lineage and catalog initiatives in partnership with Data Officers and CDOs.
• Architecture Delivery & Oversight :
• Guide design of scalable data pipelines (batch/real-time), master data management and analytics layers.
• Oversee data platform modernization and cloud migration programs.
• Provide architectural governance and quality assurance throughout project lifecycle.
• Team Leadership & Capability Building :
• Mentor and manage a team of data engineers and solution architects.
• Contribute to internal knowledge assets, accelerators and reusable frameworks.
• Client Engagement & Business Development :
• Support pre-sales and proposal activities by shaping data architecture solutions.
• Build trusted relationships with client executives and technology teams.

Required Skills and Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering or related field.
• 12 years of experience in data architecture, data engineering or information management.
• Proven experience with:
• Cloud-native data platforms (e.g., Azure Synapse, Databricks, Snowflake, BigQuery)
• ETL/ELT tools (e.g., Informatica, Talend, dbt)
• Data governance tools (e.g., Collibra, Alation, Purview)
• Big data and streaming technologies (e.g., Kafka, Spark)
• Benefits:
• Competitive tax-free salary and performance bonus.
• Exposure to cutting-edge data transformation projects in the region.
• Fast-paced, collaborative and diverse working environment.
• Opportunities for leadership growth and continuous learning.
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