62 Etl Processes jobs in the United Arab Emirates

We are seeking a visionary Data Engineering Leader to spearhead the design, development, and maintenance of our data governance, platforms, and tools. This senior role requires a technology leader with 15+ years of software development experience, including 10+ years of application architecture expertise.

The ideal candidate will possess in-depth knowledge of data platforms, machine learning, artificial intelligence, and analytics. They will be responsible for providing strategic architecture leadership, hands-on development, and serving as a subject matter expert in machine learning, AI, and data modeling to drive business insights.

• Design and build scalable data governance frameworks, ensuring seamless data flow across platforms.
• Leverage latest technologies for managing data platforms, machine learning & analytics, and drive innovation in these areas.
• Develop and implement Web Services (REST/SOAP), Service Oriented Architecture, big data, and cloud computing solutions.
• Lead data architecture initiatives, driving successful outcomes and continuous improvement.

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:

• Create backend services that optimize data processing for IoT applications.
• Collaborate with cross-functional teams to develop and implement new features.
• Maintain and improve existing systems, ensuring high performance and quality.
• Analyze application performance, identify bottlenecks, and resolve issues promptly.
• Enhance code organization, maintainability, and automation practices.

Requirements:

• Proven experience in backend software development or similar role.
• Demonstrated expertise in programming languages such as PHP and Python.
• Strong knowledge of MySQL and database management systems.
• Familiarity with RESTful APIs and web services.
• Understanding of software development principles and best practices.
• Excellent problem-solving skills and ability to work effectively in a team.

We seek a highly skilled Data Engineering Leader to drive our organization's data strategy forward. The ideal candidate will have in-depth expertise in designing and optimizing scalable data pipelines, leveraging modern cloud-based technologies.

• Design, build, and maintain reliable, high-performance data pipelines.
• Develop and optimize ETL/ELT processes for large-scale structured and unstructured data.
• Implement data models and warehouse solutions with a focus on Snowflake.
• Integrate and process data from diverse sources including SQL and NoSQL databases.
• Evaluate data quality, governance, and security standards across all systems.
• Collaborate with data scientists and ML engineers to prepare data for advanced analytics and GenAI models.
• Work closely with business stakeholders to translate requirements into actionable data engineering solutions.

• Experience: 7–10+ years of professional experience in data engineering.
• Programming: Proficiency in Python is mandatory.
• Data Engineering: Strong SQL expertise; experience with NoSQL databases; advanced skills in data modeling, ETL/ELT processes, and orchestration tools (e.g., Airflow, cloud-native services).
• Cloud: Hands-on experience with cloud data warehousing, data lakes, and related services is mandatory.
• Snowflake: Proven experience designing and managing data pipelines/warehousing in Snowflake.
• Big Data: Experience handling large volumes of structured and unstructured data.
• Desired Skills: Familiarity with preparing data for ML/GenAI workloads; knowledge of data governance and data quality frameworks.

This role offers the opportunity to drive impactful change in a dynamic environment, leveraging the latest technologies to improve data management and analysis capabilities.

In this position, you will have the chance to develop your skills further, working collaboratively with cross-functional teams to deliver innovative data-driven solutions.

We are seeking a skilled Data Engineering Specialist to join our team.

• Data engineering tools (Python, SQL, ETL) for data extraction, transformation, and loading will be the primary focus of this role.
• Data visualization tools like Power BI, Tableau, and Cognos Analytics are used in conjunction with these tools.
• The use of IBM Products like DataStage, Db2, Cloud Pak for Data is also expected.
• A knowledge of Data Lakehouse and open-source tools like Hive, Iceberg, Spark, Presto, and Parquet is necessary.
• Data Cataloging, Governance, Quality, Privacy and Lineage play a crucial role in this position.

• 7+ years of experience in data engineering and data visualization are required.
• A Bachelor's degree in Computer Science or similar field is necessary.

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.

We are seeking a Data Engineering Specialist to execute our growth hacking strategy and contribute to the development of advanced data analytics.

• Growth Strategy Execution: Design and implement data-driven strategies to boost product adoption and market penetration.
• Data Analysis: Extract meaningful business insights from quantitative and qualitative data, identifying areas for improvement and opportunities for growth.
• Experimentation and Visualization: Utilize data visualization techniques to gain valuable insights into target audiences, informing future marketing efforts.
• Ecosystem Development: Collaborate with stakeholder teams to enhance the data and tool ecosystem, ensuring seamless integration and maximum impact.

You will thrive in this role if you have a passion for technology, innovation, and collaboration. We value candidates who are driven to learn, grow, and make a lasting impact on our team's success.

• Professional Growth Opportunities
• Diverse and Inclusive Team Environment
• Competitive Compensation Package

Join to apply for the Manager - Data Engineering role at Department of Finance – Abu Dhabi .

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About the Department of Finance – Abu Dhabi

Established in 1966 with the objective of strengthening the financial sustainability of the Emirate, DoF is responsible for the development and execution of the Abu Dhabi government's annual budget and for overseeing government returns, expenditures,

Objective: Take ownership of the strategy, architecture, and delivery of a secure, AI-optimized data platform. This platform will modernize the legacy state, institute data-as-a-product governance, and enable high-scale operations. It will align with the Department of Finance's Data Strategy and AI vision, positioning the department as the regional benchmark for data-driven public finance excellence.

• Architect and oversee end to end Azure data platforms 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 (ADF pipelines/data flows, Spark, Delta Live Tables) with automated CI/CD.
• Lead migration of legacy EDWs and SSIS/ETL workloads (SQL Server, Teradata, Hadoop) 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 defining 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 enforce 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 and responsibilities as requested by the Executive Director or management.
• Provide the necessary support to the direct manager, and perform any other related tasks as requested.

• Bachelor's degree in computer science, business analytics or a similar field relevant to the job duties.
• A specialized certificate in the field of the job is preferred.
• Preferable to have 10-14 years of experience in a similar field/position.
• At least 5 years' experience in end-to-end data-engineering, and architecting cloud data platforms on Azure
• Preferable experience with financial domain.
• Expert in Azure Data Factory (pipelines, dataflows, CI/CD), data bricks or similar, Analytics, Data Lake Gen2, Delta & parquet formats.
• Designs and executes enterprise data strategy & maturity roadmaps from "ad-hoc reporting" to fully productised, governed data services.
• Proven track record building domain-aligned data marts / semantic layers that power BI, AI and real-time decisioning at scale (> 100 TB).
• Led migration of legacy EDWs & SSIS/ETL workloads (SQL Server, Teradata, Hadoop) to Azure; balances lift-and-shift with refactor to ELT/Spark.
• Champions a "data-as-a-product" mindset—defines ownership, SLAs, observability, lineage (Purview) and versioned contract-driven datasets.
• Hands-on with modern stack: Databricks / Spark, Delta Live Tables, dbt, Kafka/Event Hubs, Azure Functions, Terraform, Ansible etc.
• Strong SQL performance tuning plus Python/Scala for orchestration and data-quality frameworks; automates tests & monitoring.
• Builds secure, cost-optimized architectures (RBAC, private endpoints, encryption, cost tagging) and drives FinOps discipline.
• Seasoned people leader, mentors cross-functional squads (data engineers, analytics engineers, platform SREs) and aligns delivery to business OKRs.

• Mid-Senior level

• Full-time

• Information Technology

• IT Services and IT Consulting