61 Nosql Database jobs in the United Arab Emirates

Property Monitor is the UAE’s leading real estate technology and market intelligence platform, recently acquired by Dubizzle Group. At Property Monitor, we empower developers, brokers, investors, and property professionals with authoritative data and powerful analytics, enabling them to make faster, smarter, and more informed decisions.

As part of Dubizzle Group, we are alongside five powerhouse brands - including market-leading platforms like Bayut and dubizzle trusted by over 123 million monthly users. Together, these brands shape how people buy, sell, and connect across real estate, classifieds, and services in the UAE and broader region.

The Data Engineer will help deliver world-class big data solutions and drive impact for the dubizzle business. You will be responsible for exciting projects covering the end-to-end data life cycle – from raw data integrations with primary and third-party systems, through advanced data modeling, to state-of-the-art data visualization and development of innovative data products.

You will have the opportunity to build and work with both batch and real-time data processing pipelines. While working in a modern cloud-based data warehousing environment alongside a team of diverse, intense and interesting co-workers, you will liaise with other teams– such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

In this role, you will:

• Raw data integrations with primary and third-party systems
• Data warehouse modelling for operational and application data layers
• Development in Amazon Redshift cluster
• SQL development as part of agile team workflow
• ETL design and implementation in Matillion ETL
• Real-time data pipelines and applications using serverless and managed AWS services such as Lambda, Kinesis, API Gateway, etc.
• Design and implementation of data products enabling data-driven features or business solutions
• Data quality, system stability and security
• Coding standards in SQL, Python, ETL design
• Building data dashboards and advanced visualisations in Periscope Data with a focus on UX, simplicity and usability
• Working with other departments on data products – i.e. product & technology, marketing & growth, finance, core business, advertising and others
• Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
• Be able to work autonomously without supervision on complex projects
• Participate in the early morning ETL status check rota

Requirements:

• Top of class technical degree such as computer science, engineering, math, physics.
• 3+ years of experience working with customer-centric data at big data-scale, preferably in an online / e-commerce context
• 2+ years of experience with one or more programming languages, especially Python
• Strong track record in business intelligence solutions, building and scaling data warehouses and data modelling
• Experience with modern big data ETL tools is a plus (e.g. Matillion)
• Experience with AWS data ecosystem (or other cloud providers)
• Experience with modern data visualization platforms such as Sisense (formerly Periscope Data), Google Data Studio, Tableau, MS Power BI etc.
• Knowledge of modern real-time data pipelines is a strong plus (e.g. server less framework, lambda, kinesis, etc.)
• Knowledge or relational relational and dimensional data models
• Knowledge of terminal operations and Linux workflows
• World-class SQL skills across a variety of relational data warehousing technologies especially in cloud data warehousing (e.g. Amazon Redshift, Google BigQuery, Snowflake, Vertica, etc.)
• Ability to communicate insights and findings to a non-technical audience

What We Offer:

• A fast paced, high performing team.
• Multicultural environment with over 50 different nationalities
• Competitive Tax-free Salary
• Comprehensive Health Insurance
• Annual Air Ticket Allowance
• Employee discounts at multiple vendors across the emirates
• Rewards & Recognitions
• Learning & Development

Dubizzle Group is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

8. Education / Qualifications / Professional Training

Bachelor’s Degree in Computer Science or Management with 4+ years of experience in Vertica and equivalent Databases

• Vertica Certification is a plus.
• Experience with data visualization tools (e.g., Power BI, SAP BI, SAS, Tableau) for data reporting and dashboard creation is beneficial.

Above 4 yrs exp required in Vertica Database Functionalities

1. Bachelor’s degree in Computer Science, Information Technology, or a related field.
2. Proven experience as a Data Engineer or similar role with hands-on expertise in designing and managing data solutions in Vertica.
3. Strong proficiency in SQL and experience with data modeling and schema design in Vertica.
4. In-depth knowledge of ETL processes and tools, particularly for data integration into Vertica.
5. Familiarity with other big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is advantageous.
6. Understanding of data warehousing concepts and best practices.
7. Experience in performance tuning and optimization of Vertica databases.
8. Familiarity with Linux environments and shell scripting for data-related automation tasks is a plus.
9. Excellent problem-solving skills and the ability to handle large datasets effectively.
10. Strong communication and collaboration skills to work effectively within a team-oriented environment.
11. Self-motivated, with the ability to work independently and manage multiple tasks and projects simultaneously.

About the Role

We are an emerging AI-native product-driven, agile start-up under Abu Dhabi government AND we are seeking a motivated and technically versatile Data Engineer to join our team. You will play a key role in delivering data platforms, pipelines, and ML enablement within a Databricks on Azure environment.

As part of a stream-aligned delivery team, you’ll work closely with Data Scientists, Architects, and Product Managers to build scalable, high-quality data solutions for clients. You'll be empowered by a collaborative environment that values continuous learning, Agile best practices, and technical excellence.

Ideal candidates have strong hands-on experience in Databricks, Python, ADF and are comfortable in fast-paced, client-facing consulting engagements.

Skills and Experience requirements
1. Technical

• Databricks (or similar) e.g. Notebooks (Python, SQL), Delta Lake, job scheduling, clusters, and workspace management, Unity Catalog, access control awareness
• Cloud data engineering – ideally Azure, including storage (e.g., ADLS, S3, ADLS), compute, and secrets management
• Development languages such as Python, SQL, C#, javascript etc. especially data ingestion, cleaning, and transformation
• ETL / ELT – including structured logging, error handling, reprocessing strategies, APIs, flat files, databases, message queues, event streaming, event sourcing etc.
• Automated testing (ideally TDD), pairing/mobbing. Trunk Based Development, Continuous Deployment and Infrastructure-as-Code (Terraform)
• Git and CI/CD for notebooks, data pipelines, and deployments

2. Integration & Data Handling

• Experienced in delivering platforms for clients – including file transfer, APIS (REST etc.), SQL/NoSQL/graph databases, JSON, CSV, XML, Parquet etc
• Data validation and profiling - assess incoming data quality. Cope with schema drift, deduplication, and reconciliation
• Testing and monitoring pipelines: Unit tests for transformations, data checks, and pipeline observability

3. Working Style

• Comfortable leveraging the best of lean, agile and waterfall approaches. Can contribute to planning, estimation, and documentation, but also collaborative daily re-prioritisation
• Able to explain technical decisions to teammates or clients
• Documents decisions and keeps stakeholders informed
• Comfortable seeking support from other teams for Product, Databricks, Data architecture
• Happy to collaborate with Data Science team on complex subsystems

Nice-to-haves

• MLflow or light MLOps experience (for the data science touchpoints)
• Dbt / dagster / airflow or similar transformation tools
• Understanding of security and compliance (esp. around client data)
• Past experience in consulting or client-facing roles

Candidate Requirements

• 5–8 years (minimum 3–4 years hands-on with cloud/data engineering, 1–2 years in Databricks/Azure, and team/project leadership exposure)
• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Data Engineering

Job Type: Full-time

Visa, Insurance, Yearly Flight Ticket, Bonus scheme, relocation logistics covered

Interviewing process consists of 2 or 3 technical/behavioral interviews

About the Role

We are seeking a motivated and technically versatile Data Engineer to join our team. You will play a key role in delivering data platforms, pipelines, and ML enablement within a Databricks on Azure environment.

As part of a stream-aligned delivery team, you’ll work closely with Data Scientists, Architects, and Product Managers to build scalable, high-quality data solutions for clients. You'll be empowered by a collaborative environment that values continuous learning, Agile best practices, and technical excellence.

Ideal candidates have strong hands-on experience in Databricks, Python, ADF and are comfortable in fast-paced, client-facing consultingengagements.

Skills and Experience requirements

• Databricks (or similar) e.g. Notebooks (Python, SQL), Delta Lake, job scheduling, clusters, and workspace management, Unity Catalog, access control awareness
• Cloud data engineering – ideally Azure, including storage (e.g., ADLS, S3, ADLS), compute, and secrets management
• Development languages such as Python, SQL, C#, javascript etc. especially data ingestion, cleaning, and transformation
• ETL / ELT – including structured logging, error handling, reprocessing strategies, APIs, flat files, databases, message queues, event streaming, event sourcing etc.
• Automated testing (ideally TDD), pairing/mobbing. Trunk Based Development, Continuous Deployment and Infrastructure-as-Code (Terraform)
  

• Git and CI/CD for notebooks, data pipelines, and deployments

2. Integration & Data Handling

• Experienced in delivering platforms for clients – including file transfer, APIS (REST etc.), SQL/NoSQL/graph databases, JSON, CSV, XML, Parquet etc
  
• Data validation and profiling - assess incoming data quality. Cope with schema drift, deduplication, and reconciliation
  
• Testing and monitoring pipelines: Unit tests for transformations, data checks, and pipeline observability

3. WorkingStyle

• Comfortable leveraging the best of lean, agile and waterfall approaches. Can contribute to planning, estimation, and documentation, but also collaborative daily re-prioritisation
• Able to explain technical decisions to teammates or clients
• Documents decisions and keeps stakeholders informed
• Comfortable seeking support from other teams for Product, Databricks, Data architecture
• Happy to collaborate with Data Science team on complex subsystems

Nice-to-haves

• MLflow or light MLOps experience (for the data science touchpoints)
• Dbt / dagster / airflow or similar transformation tools
• Understanding of security and compliance (esp. around client data)
• Past experience in consulting or client-facing roles

Candidate Requirements

• 5–8 years (minimum 3–4 years hands-on with cloud/data engineering, 1–2 years in Databricks/Azure, and team/project leadership exposure)
• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Data Engineering

Disclaimer:

This job posting is not open to recruitment agencies. Any candidate profile submitted by a recruitment agency will be considered as being received directly from an applicant. Contango reserves the rights to contact the candidate directly, without incurring any obligations or liabilities for payment of any fees to the recruitment agency.

Location : Dubai

Who Can Apply: Candidates who are currently in Dubai
Job Type: Contract
Experience: Minimum 8+ years

Job Summary:

We are looking for an experienced Data Engineer to design, develop, and optimize data pipelines, ETL processes, and data integration solutions. The ideal candidate should have expertise in AWS cloud services, data engineering best practices, open-source tools, and data schema design. The role requires hands-on experience with large-scale data processing, real-time data streaming, and cloud-based data architectures.

Key Responsibilities:

• Develop and Maintain Data Pipelines to process structured and unstructured data efficiently.
• Implement ETL/ELT Workflows for batch and real-time data processing.
• Optimize Data Processing Workflows using distributed computing frameworks.
• Ensure Data Integrity and Quality through data validation, cleaning, and transformation techniques.
• Work with AWS Cloud Services , including S3, Redshift, Glue, Lambda, DynamoDB, and Kinesis.
• Leverage Open-Source Tools like Apache Spark, Airflow, Kafka, and Flink for data processing.
• Manage and Optimize Database Performance for both SQL and NoSQL environments.
• Collaborate with Data Scientists and Analysts to enable AI/ML model deployment and data accessibility.
• Support Data Migration Initiatives from on-premise to cloud-based data platforms.
• Ensure Compliance and Security Standards in handling sensitive and regulated data.
• Develop Data Models and Schemas for efficient storage and retrieval.

Required Skills & Qualifications:

• 8+ years of experience in data engineering, data architecture, and cloud computing.
• Strong knowledge of AWS Services such as Glue, Redshift, Athena, Lambda, and S3.
• Expertise in ETL Tools , including Talend, Apache NiFi, Informatica, dbt, and AWS Glue.
• Proficiency in Open-Source Tools such as Apache Spark, Hadoop, Airflow, Kafka, and Flink.
• Strong Programming Skills in Python, SQL, and Scala.
• Experience in Data Schema Design , normalization, and performance optimization.
• Knowledge of Real-time Data Streaming using Kafka, Kinesis, or Apache Flink.
• Experience in Data Warehouse and Data Lake Solutions .
• Hands-on experience with DevOps and CI/CD Pipelines for data engineering workflows.
• Understanding of AI and Machine Learning Data Pipelines .
• Strong analytical and problem-solving skills .

Preferred Qualifications:

• AWS Certified Data Analytics – Specialty or AWS Solutions Architect certification.
• Experience with Kubernetes, Docker, and serverless data processing.
• Exposure to MLOps and data engineering practices for AI/ML solutions.
• Experience with distributed computing and big data frameworks.

The Data Engineer will be responsible for developing semantic models on top of the Data Lake/Data Warehouse to fulfill the self-service BI foundation requirements. This includes data extraction from various data sources and integration into the central data lake/data warehouse using enterprise platforms like Informatica iPaaS.

1. Designing data warehouse data models based on business requirements.
2. Designing, developing, and testing both batch and real-time Extract, Transform and Load (ETL) processes required for data integration.
3. Ingesting both structured and unstructured data into the SMBU data lake/data warehouse system.
4. Designing and developing semantic models/self-service cubes.
5. Performing BI administration and access management to ensure access and reports are properly governed.
6. Performing unit testing and data validation to ensure business UAT is successful.
7. Performing ad-hoc data analysis and presenting results in a clear manner.
8. Assessing data quality of the source systems and proposing enhancements to achieve a satisfactory level of data accuracy.
9. Optimizing ETL processes to ensure execution time meets requirements.
10. Maintaining and architecting ETL pipelines to ensure data is loaded on time on a regular basis.

1. 5 to 8 years of overall experience.
2. Proven experience in the development of dimensional models in Azure Synapse with strong SQL knowledge.
3. Minimum of 3 years working as a Data Engineer in the Azure ecosystem specifically using Synapse, ADF & Data bricks.
4. Preferably 3 years of experience with data warehousing, ETL development, SQL Queries, Synapse, ADF, PySpark, and Informatica iPaaS for data ingestion & data modeling.

Bayut & dubizzle have the unique distinction of being iconic, homegrown brands with a strong presence across the seven emirates in the UAE. Connecting millions of users across the country, we are committed to delivering the best online search experience.

As part of Dubizzle Group, we are alongside some of the strongest classified brands in the market. With a collective strength of 8 brands, we have more than 160 million monthly users that trust in our dedication to providing them with the best platform for their needs.

The Data Engineer intern will be participating in exciting projects covering the end-to-end data lifecycle – from raw data integrations with primary and third-party systems, through advanced data modelling, to state-of-the-art data visualisation and development of innovative data products.

You will have the opportunity to learn how to build and work with both batch and real-time data processing pipelines. You will work in a modern cloud-based data warehousing environment alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments – such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

Key Responsibilities Include:

1. Raw data integrations with primary and third-party systems
2. Data warehouse modelling for operational and application data layers
3. Development in Amazon Redshift cluster
4. SQL development as part of agile team workflow
5. ETL design and implementation in Matillion ETL
6. Design and implementation of data products enabling data-driven features or business solutions
7. Data quality, system stability and security
8. Coding standards in SQL, Python, ETL design
9. Building data dashboards and advanced visualisations in Periscope Data with a focus on UX, simplicity and usability
10. Working with other departments on data products – i.e. product & technology, marketing & growth, finance, core business, advertising and others
11. Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data

Minimum Requirements:

• Bachelor’s degree in computer science, engineering, math, physics or any related quantitative field.
• Knowledge of relational and dimensional data models
• Knowledge of terminal operations and Linux workflows
• Ability to communicate insights and findings to a non-technical audience
• Good SQL skills across a variety of relational data warehousing technologies especially in cloud data warehousing (e.g. Amazon Redshift, Google BigQuery, Snowflake, Vertica, etc.)
• Attention to details and analytical thinking
• Entrepreneurial spirit and ability to think creatively; highly-driven and self-motivated; strong curiosity and strive for continuous learning
• Ability to contribute to a platform used by more than 5M users in UAE and other platforms in the region.

Bayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Overview

Job Title: Vertica Data Engineer

Job Type: Full-time

Location: On-site Dubai, Dubai, United Arab Emirates

As a Vertica Data Engineer, you will be responsible for architecting, developing, and maintaining our Vertica database systems and data pipelines. You will work closely with cross-functional teams, including data scientists, analysts, and developers, to ensure seamless data integration, transformation, and retrieval from Vertica. Your expertise in Vertica's architecture, ETL processes, data modeling, and performance tuning will be crucial in delivering robust and scalable data solutions to support our business objectives. Responsible to migrate data from Oracle, SQL Server to VERTICA Database on timely manner.

• Design and implement efficient data pipelines to extract, transform, and load (ETL) data from various sources into Vertica using popular ETL tools like SAP BODS and Informatica.
• Develop and maintain data models and database structures optimized for high-performance data retrieval and analysis in Vertica.
• Experience in migrating data from Oracle/SQL Server/SQ Lite to Vertica database.
• Write program units (functions/procedures) to prepare data based on business requirements.
• Collaborate with data scientists and analysts to understand their data needs and provide scalable solutions to meet analytical requirements.
• Implement data quality checks and data validation processes to ensure the accuracy and integrity of data stored in Vertica.
• Experience in VerticaPy to work with machine learning libraries for data science use cases.
• Work with the DevOps team to ensure smooth deployment, monitoring, and maintenance of Vertica instances.
• Optimize database performance and query execution through indexing, partitioning, and other performance tuning techniques.
• Monitor Vertica database health, troubleshoot performance issues, and proactively address potential bottlenecks.
• Collaborate with data engineers and other stakeholders to define best practices and data governance standards for Vertica usage.
• Stay up-to-date with the latest advancements in Vertica and big data technologies and recommend improvements to existing solutions.
• Document technical specifications, data flows, and architectural designs related to Vertica implementations.
• Provide training and support to end-users to enable them to navigate and interact with Power BI reports effectively.

1. Bachelor's degree in Computer Science, Information Technology, or a related field.
2. Proven experience as a Data Engineer or similar role with hands-on expertise in designing and managing data solutions in Vertica.
3. Strong proficiency in SQL and experience with data modeling and schema design in Vertica.
4. In-depth knowledge of ETL processes and tools, particularly for data integration into Vertica.
5. Familiarity with other big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is advantageous.
6. Understanding of data warehousing concepts and best practices.
7. Experience in performance tuning and optimization of Vertica databases.
8. Familiarity with Linux environments and shell scripting for data-related automation tasks is a plus.
9. Excellent problem-solving skills and the ability to handle large datasets effectively.
10. Strong communication and collaboration skills to work effectively within a team-oriented environment.
11. Self-motivated, with the ability to work independently and manage multiple tasks and projects simultaneously.

Position Overview

We're seeking a self-sufficient Senior Data Engineer to build and scale our data infrastructure supporting product, engineering and analytics team. You'll architect data pipelines, optimize our data platform, and ensure the teams have reliable, high-quality data to drive business decisions.

This is a hands-on role for someone who can own the entire data engineering stack - from ingestion to transformation to orchestration. You'll work independently to solve complex data challenges and build scalable solutions.

Core Responsibilities

• Data Pipeline Development & Optimization : Design, build, and maintain scalable data pipelines using Spark and Databricks
• Develop ETL/ELT workflows to process large volumes of customer behavior data
• Optimize Spark jobs for performance, cost efficiency, and reliability
• Build real-time and batch data processing solutions
• Implement data quality checks and monitoring throughout pipelines
• Ensure data freshness and SLA compliance for analytics workloads

AWS Data Infrastructure

• Architect and manage data infrastructure on AWS (S3, Glue, EMR, Redshift)
• Design and implement data lake architecture with proper partitioning and optimization
• Configure and optimize AWS Glue for ETL jobs and data cataloging
• Shifting Glue jobs to Zero ETL
• Implement security best practices for data access and governance
• Monitor and optimize cloud costs related to data infrastructure

Data Modeling & Architecture

• Design and implement dimensional data models for analytics
• Build star/snowflake schemas optimized for analytical queries
• Create data marts for specific business domains (retention, campaigns, product)
• Ensure data model scalability and maintainability
• Document data lineage, dependencies, and business logic
• Implement slowly changing dimensions and historical tracking

Orchestration & Automation

• Build and maintain workflow orchestration using Airflow or similar tools
• Implement scheduling, monitoring, and alerting for data pipelines
• Create automated data quality validation frameworks
• Design retry logic and error handling for production pipelines
• Build CI/CD pipelines for data workflows
• Automate infrastructure provisioning using Infrastructure as Code

Cross-Functional Collaboration

• Partner with Senior Data Analyst to understand analytics requirements
• Work with Growth Director and team to enable data-driven decision making
• Support CRM Lead with data needs for campaign execution
• Collaborate with Product and Engineering on event tracking and instrumentation
• Document technical specifications and best practices for the team
• Work closely with all squads, establish data contracts with engineers to land data in a most optimal way

Required Qualifications

• Must-Have Technical Skills
• Apache Spark : Expert-level proficiency in PySpark/Spark SQL for large-scale data processing
• Databricks : Strong hands-on experience building and optimizing pipelines on Databricks platform
• AWS : Deep knowledge of AWS data services (S3, Glue, EMR, Redshift, Athena)
• Data Modeling : Proven experience designing dimensional models and data warehouses
• Orchestration : Strong experience with workflow orchestration tools (Airflow, Prefect, or similar)
• SQL : Advanced SQL skills for complex queries and optimization
• Python : Strong programming skills for data engineering tasks
• Experience
• 6-10 years in data engineering with focus on building scalable data platforms
• Proven track record architecting and implementing data infrastructure from scratch
• Experience processing large volumes of event data (billions of records)
• Background in high-growth tech companies or consumer-facing products
• Experience with mobile/web analytics data preferred
• Technical Requirements
• Expert in Apache Spark (PySpark and Spark SQL) with performance tuning experience
• Deep hands-on experience with Databricks (clusters, jobs, notebooks, Delta Lake)
• Strong AWS expertise: S3, Glue, EMR, Redshift, Athena, Lambda, CloudWatch
• Proficiency with orchestration tools: Airflow, Prefect, Step Functions, or similar
• Advanced data modeling skills: dimensional modeling, normalization, denormalization
• Experience with data formats: Parquet, Avro, ORC, Delta Lake
• Version control with Git and CI/CD practices
• Infrastructure as Code: Terraform, CloudFormation, or similar
• Understanding of data streaming technologies (Kafka, Kinesis) is a plus
• Core Competencies
• Self-sufficient : You figure things out independently without constant guidance
• Problem solver : You diagnose and fix complex data pipeline issues autonomously
• Performance-focused : You optimize for speed, cost, and reliability
• Quality-driven : You build robust, maintainable, and well-documented solutions
• Ownership mindset : You take end-to-end responsibility for your work
• Collaborative : You work well with analysts and business stakeholders despite being independent
• Nice-to-Have
• Databricks certifications (Data Engineer Associate/Professional)
• Experience with dbt for data transformation
• Knowledge of customer data platforms (Segment, mParticle, Rudderstack)
• Experience with event tracking platforms (Mixpanel, Amplitude)
• Familiarity with machine learning infrastructure and MLOps
• Experience in MENA region or emerging markets
• Background in on-demand services, marketplaces, or subscription businesses
• Knowledge of real-time streaming architectures

What We Offer

• Competitive salary based on experience
• Ownership of critical data infrastructure and architecture decisions
• Work with modern data stack and cutting-edge AWS technologies
• Direct impact on business decisions through data platform improvements
• Comprehensive health benefits