74 Data Driven Products jobs in Dubai

Data Architect

We are seeking a skilled and experienced Data Architect to design and implement data solutions that support our business goals. As a key member of our team, you will play a critical role in ensuring the success of our data-driven initiatives.

• Design Scalable Data Architectures : Create robust and scalable data architectures aligned with business objectives.
• Develop Integrated Data Solutions : Design, develop, and manage integrated data solutions that meet business needs.
• Collaborate with Cross-Functional Teams : Work closely with data engineers, data analysts, and stakeholders to ensure seamless data integration and quality.
• Implement Data Governance and Best Practices : Develop and implement data governance policies and best practices for data management.
• Optimize Database Performance : Ensure efficient data storage and retrieval by optimizing database performance.
• Stay Current with Emerging Trends : Stay up-to-date with emerging trends and technologies in data architecture.
• Provide Technical Guidance : Provide technical guidance and support to cross-functional teams.

• Bachelor's or Master's Degree : Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
• 5+ Years of Experience : 5+ years of experience in data architecture or a related role.
• Strong Knowledge of Data Modeling Concepts : Strong knowledge of data modeling concepts, database design, and data management best practices.
• Experience with SQL and NoSQL Databases : Experience with SQL and NoSQL databases.
• Familiarity with ETL/ELT Processes : Familiarity with ETL/ELT processes and data integration tools.
• Excellent Problem-Solving Skills : Excellent problem-solving skills and attention to detail.
• Effective Communication and Collaboration Skills : Effective communication and collaboration skills.
• Ability to Work in a Fast-Paced Environment : Ability to work in a fast-paced environment and manage multiple priorities.

• Paid Time Off
• Performance Bonus
• Training & Development

Mid-Senior Level

Contract

IT Services and IT Consulting

Architect

Job Title: Data Engineering Lead

We are seeking a highly skilled Data Engineering Lead to join our team. As a key member of the engineering team, you will be responsible for designing and building scalable data systems, including data lakes, ingestion pipelines, and storage solutions.

• Design and Build Scalable Data Systems: Design and build scalable data systems that can handle large volumes of structured and unstructured data.
• Ingestion Pipelines: Architect batch/stream pipelines using modern orchestration tools such as Airflow and streaming platforms like Kafka.
• Storage Solutions: Implement and tune S3 column-oriented and time-series data storage for petabyte-scale analytics.
• Tooling and Libraries: Develop internal libraries for schema management, data contracts validation, and lineage.
• Reliability and Observability: Embed monitoring, alerting, SLAs, SLOs, and CI/CD to ensure data reliability and observability.
• Collaboration: Partner with cross-functional teams to translate requirements into platform capabilities.

Required Skills and Qualifications:

• 6 years of experience building and maintaining production-grade data systems.
• Expert-level Python development skills, with knowledge of Go and C.
• Hands-on experience with modern orchestration tools and streaming platforms.
• Advanced SQL skills, including complex aggregations and query optimisation.
• Experience designing high-throughput APIs and data access libraries.
• Solid fundamentals in Linux containerisation and cloud object storage solutions.
• Strong knowledge of handling diverse data formats and storage strategies.
• English language proficiency at C1 level.

Job Title: Data Engineering Specialist

About the Role

This is a key position within our data operations team, focused on developing and maintaining data infrastructure. As a Data Engineering Specialist, you will collaborate with end-users to design and implement reporting systems that provide actionable insights for informed decision-making.

The ideal candidate will have strong understanding of data engineering concepts, including data pipelines, ETL processes, and data modeling. Proficiency in programming languages such as Python, Java, or Scala is required.

In this role, you will create comprehensive dashboards and interactive visualizations using enterprise BI platforms. You will also design and develop data narratives and analytical reports to effectively communicate business performance, trends, and recommendations to stakeholders.

You will work closely with the Data Manager to support AWS services such as AWS Glue, AWS Data Pipeline, and Amazon S3. Your goal will be to build robust data processing workflows and API gateways.

To succeed in this role, you must have a bachelor's degree in computer science, software engineering, or a related field. At least 2 years of experience in a BI Developer or Data Engineering role for an eCommerce, transaction-based Retailer is required.

We are seeking a highly skilled and detail-oriented individual who can deliver high-quality results under tight deadlines. If you have a passion for data engineering and want to contribute to a dynamic team, we encourage you to apply.

Architect and oversee end to end Azure data platforms, including Data Factory, Databricks or similar, ensuring scalability, security, and cost efficiency. Define and execute the enterprise data strategy and maturity roadmap, moving the organization from ad hoc reporting to fully productized, governed data services. Design, build, and manage high throughput data pipelines and ELT workflows with automated CI / CD. Lead migration of legacy EDWs and SSIS / ETL workloads to modern Azure architectures, balancing lift and shift and refactor approaches. Develop domain-aligned data marts and semantic layers powering BI, AI, and real time decisioning at 100 TB scale .

Champion a "data as a product" operating model with dataset ownership, SLAs, observability, lineage (Purview), and version-controlled contracts. Implement robust data quality frameworks, test automation, and performance tuning in SQL, Python, and Scala to guarantee reliable, audit-ready data. Establish secure architectures with RBAC, private endpoints, encryption, and FinOps practices for optimal spend management. Integrate streaming and event-driven data (Kafka / Event Hubs, Azure Functions) into real time analytics and AI workloads. Mentor and lead cross-functional squads of data engineers, analytics engineers, and SREs; align delivery to business OKRs and foster a culture of continuous improvement. Engage finance and analytics stakeholders to translate business requirements into governed, reusable data products and services. Perform other duties as requested by leadership.

Qualifications and Experience Required

As the Head of Data Engineering, you will be responsible for designing, implementing, and maintaining a robust, scalable, and compliant data architecture that supports our exchange’s operations, analytics, and regulatory reporting requirements. You will lead a team of data engineers, ensuring high availability, security, and performance of our data infrastructure. You will work closely with stakeholders across technology, compliance, risk, and product teams to develop data pipelines, warehouses, and real-time analytics capabilities.

This is a strategic yet hands-on role where you will drive data engineering best practices, scalability, and automation while ensuring compliance with regulatory data requirements for a financial services entity.

Data Architecture & Strategy :

1. Define and own the data architecture strategy for the exchange, ensuring it is scalable, secure, and regulatory-compliant.
2. Design and implement data modeling, governance, and security frameworks to meet financial and regulatory requirements.
3. Architect real-time and batch processing data pipelines to handle trade data, order books, user activity, and market analytics.
4. Optimize data storage and retrieval for performance and cost efficiency, leveraging cloud-based and hybrid solutions.
5. Build and maintain ETL / ELT data pipelines for operational, analytical, and compliance-related data.
6. Ensure high data quality, reliability, and availability through robust monitoring, alerting, and data validation techniques.
7. Manage and enhance data warehouses, data lakes, and streaming platforms to support business intelligence and machine learning use cases.
8. Oversee database design and optimization for transactional and analytical workloads (e.g., Aurora, Redis, Kafka).
9. Implement data lineage, metadata management, and access control mechanisms in line with compliance requirements.

Compliance, Security & Risk Management :

1. Work closely with compliance and risk teams to ensure data retention policies, audit trails, and reporting mechanisms meet regulatory requirements (e.g., FATF, AML, GDPR, MiCA).
2. Implement encryption, anonymization, and access control policies to safeguard sensitive user and transaction data.
3. Support fraud detection and risk monitoring through data analytics and alerting frameworks.

Leadership & Team Management :

1. Lead, mentor, and grow a small team of data engineers, fostering a culture of collaboration, innovation, and accountability.
2. Drive best practices in data engineering, DevOps for data, and CI / CD automation for analytics infrastructure.
3. Collaborate with software engineers, DevOps, data analysis, and product teams to integrate data solutions into the broader exchange ecosystem.

Technical competencies and skills :

1. Proven experience in data architecture and engineering, preferably within a regulated financial or crypto environment.
2. Strong proficiency in SQL, Python, or Scala for data engineering.
3. Experience with cloud-based data platforms (AWS, GCP, or Azure) and orchestration tools (Airflow, Prefect, Dagster).
4. Hands-on experience with real-time data processing (Kafka, Pulsar, Flink, Spark Streaming).
5. Expertise in data warehousing solutions (Snowflake, BigQuery, Redshift, Databricks).
6. Strong understanding of database design, indexing strategies, and query optimization.
7. Experience implementing data governance, lineage, and cataloging tools.
8. Familiarity with blockchain / crypto data structures and APIs is a plus.

Leadership & Strategic Skills :

1. Experience leading and mentoring a team of data engineers.
2. Ability to design data strategies that align with business goals and regulatory requirements.
3. Strong cross-functional collaboration skills with compliance, risk, and technology teams.
4. Ability to work in a fast-paced, high-growth startup environment with a hands-on approach.

Industry & Compliance Knowledge :

1. Experience in regulated financial markets, fintech, or crypto is highly preferred.
2. Familiarity with financial data standards, KYC / AML reporting, and regulatory requirements related to data handling.

Preferred Qualifications :

1. Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.
2. Certifications in cloud data engineering (AWS / GCP / Azure), data governance, or security are a plus.
3. Experience working in a crypto exchange, trading platform, or high-frequency trading environment is an advantage.

At M2, we believe in a workplace where talent, dedication, and passion are the only factors that count, regardless of gender, background, age, and other characteristics. We embrace diversity because we know that it fuels innovation, fosters creativity, and drives success. So, if you're ready to join a team where your potential is truly valued, welcome aboard!

We are seeking a seasoned Cloud Solutions Architect to lead the design and deployment of scalable cloud-based data platforms.

As the Head of Data Engineering, you will be responsible for designing, implementing, and maintaining a robust, scalable, and compliant data architecture that supports our exchange's operations, analytics, and regulatory reporting requirements. You will lead a team of data engineers, ensuring high availability, security, and performance of our data infrastructure. You will work closely with stakeholders across technology, compliance, risk, and product teams to develop data pipelines, warehouses, and real-time analytics capabilities.

This is a strategic yet hands-on role where you will drive data engineering best practices, scalability, and automation while ensuring compliance with regulatory data requirements for a financial services entity.

Data Architecture & Strategy :

1. Define and own the data architecture strategy for the exchange, ensuring it is scalable, secure, and regulatory-compliant.
2. Design and implement data modeling, governance, and security frameworks to meet financial and regulatory requirements.
3. Architect real-time and batch processing data pipelines to handle trade data, order books, user activity, and market analytics.
4. Optimize data storage and retrieval for performance and cost efficiency, leveraging cloud-based and hybrid solutions.
5. Build and maintain ETL / ELT data pipelines for operational, analytical, and compliance-related data.
6. Ensure high data quality, reliability, and availability through robust monitoring, alerting, and data validation techniques.
7. Manage and enhance data warehouses, data lakes, and streaming platforms to support business intelligence and machine learning use cases.
8. Oversee database design and optimization for transactional and analytical workloads (e.g., Aurora, Redis, Kafka).
9. Implement data lineage, metadata management, and access control mechanisms in line with compliance requirements.

Compliance, Security & Risk Management :

1. Work closely with compliance and risk teams to ensure data retention policies, audit trails, and reporting mechanisms meet regulatory requirements (e.g., FATF, AML, GDPR, MiCA).
2. Implement encryption, anonymization, and access control policies to safeguard sensitive user and transaction data.
3. Support fraud detection and risk monitoring through data analytics and alerting frameworks.

Leadership & Team Management :

1. Lead, mentor, and grow a small team of data engineers, fostering a culture of collaboration, innovation, and accountability.
2. Drive best practices in data engineering, DevOps for data, and CI / CD automation for analytics infrastructure.
3. Collaborate with software engineers, DevOps, data analysis, and product teams to integrate data solutions into the broader exchange ecosystem.

Technical competencies and skills :

1. Proven experience in data architecture and engineering, preferably within a regulated financial or crypto environment.
2. Strong proficiency in SQL, Python, or Scala for data engineering.
3. Experience with cloud-based data platforms (AWS, GCP, or Azure) and orchestration tools (Airflow, Prefect, Dagster).
4. Hands-on experience with real-time data processing (Kafka, Pulsar, Flink, Spark Streaming).
5. Expertise in data warehousing solutions (Snowflake, BigQuery, Redshift, Databricks).
6. Strong understanding of database design, indexing strategies, and query optimization.
7. Experience implementing data governance, lineage, and cataloging tools.
8. Familiarity with blockchain / crypto data structures and APIs is a plus.

Leadership & Strategic Skills :

1. Experience leading and mentoring a team of data engineers.
2. Ability to design data strategies that align with business goals and regulatory requirements.
3. Strong cross-functional collaboration skills with compliance, risk, and technology teams.
4. Ability to work in a fast-paced, high-growth startup environment with a hands-on approach.

Industry & Compliance Knowledge :

1. Experience in regulated financial markets, fintech, or crypto is highly preferred.
2. Familiarity with financial data standards, KYC / AML reporting, and regulatory requirements related to data handling.

Preferred Qualifications :

1. Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.
2. Certifications in cloud data engineering (AWS / GCP / Azure), data governance, or security are a plus.
3. Experience working in a crypto exchange, trading platform, or high-frequency trading environment is an advantage.

At M2, we believe in a workplace where talent, dedication, and passion are the only factors that count, regardless of gender, background, age, and other characteristics. We embrace diversity because we know that it fuels innovation, fosters creativity, and drives success. So, if you're ready to join a team where your potential is truly valued, welcome aboard

Job Title: Enterprise Data Engineering Leader

Lead the design and implementation of large-scale data solutions, provide strategic guidance on data architecture, and drive cross-functional collaboration.

• Develop robust ETL pipelines and data solutions that scale with business needs.
• Collaborate with data analysts, BI developers, product owners, and IT teams to deliver high-quality data products.
• Design and optimize data workflows using tools such as IBM DataStage, Talend, Informatica, and Databricks.
• Implement data integration solutions for structured and unstructured data across on-premise and cloud platforms.

Required Skills:

• Bachelor's degree in Engineering, Computer Science, or a related field (MTech in Data Science is a plus).
• 8+ years of hands-on experience in ETL development and data engineering.
• Strong proficiency with tools: IBM DataStage, Talend, Informatica, Databricks, Power BI, Tableau.
• Strong SQL, PL/I, Python, and Unix Shell scripting skills.
• Experience with cloud platforms like AWS and modern big data tools like Hadoop, Spark.
• Solid understanding of data warehousing, data modeling, and data migration practices.
• Experience working in Agile/Scrum environments.
• Excellent problem-solving, communication, and team collaboration skills.

Key Responsibilities:

• Drive strategic data initiatives and ensure alignment with business goals.
• Collaborate with cross-functional teams to deliver high-quality data products.
• Develop and implement large-scale data solutions that meet business needs.

We are seeking a highly skilled professional to lead our data engineering efforts.

This is an exciting opportunity to design, build, and maintain robust data pipelines and visualization solutions that will drive critical business insights.

• Data Pipeline Development : Design, develop, and maintain scalable ETL pipelines using SSIS and/or Informatica.
• Data Modeling : Create and optimize data models for efficient data storage and retrieval.
• Data Visualization : Develop interactive and insightful data visualizations and reports using Power BI Desktop and Power BI Service.
• Gateway Management : Implement and manage Power BI gateways for secure and reliable data access.
• Database Performance Tuning : Write and optimize complex SQL queries, stored procedures, and perform database performance tuning.

• BI Experience : 8-10 years of experience in the BI & Analytics domain with a focus on data engineering.
• ETL Expertise : Minimum 4 years of hands-on experience building ETL pipelines using SSIS and/or Informatica.
• Power BI Proficiency : Minimum 3 years of experience developing and deploying data visualizations using Power BI.
• Technical Skills : Strong proficiency in database concepts, data modeling, and advanced SQL development.
• Problem-Solving : Proven track record of developing and deploying data integration and reporting solutions to production.
• Critical Thinking : Excellent analytical, problem-solving, and communication skills.