etl developer

bankfab

<div><div>Job Description</div>
<div>
<p><b>Responsibilities:
</b></p><ul><li>Design, implement, and maintain robust ETL/ELT processes to ingest, clean, and transform data from multiple sources
</li></ul><ul><li>Process and manage complex datasets to support business and analytical needs
</li></ul><ul><li>Conduct regular testing and enhancement of data pipelines to improve efficiency
</li></ul><ul><li>Implement best practices for data validation, testing, and monitoring, proactively identifying and resolving issues to maintain data integrity
</li></ul><ul><li>Collaborate with software engineers and AI/ ML engineers to ensure seamless data accessibility
</li></ul><ul><li>Implement best practices for data governance, security, and quality assurance
</li></ul><ul><li>Document data architectures, lineage, and metadata to ensure transparency and reproducibility
</li></ul><p></p><p><b>Qualifications:
</b></p><ul><li>5+ years of experience in data engineering, ETL development, or data warehousing
</li></ul><ul><li>Demonstrated ability to design and manage ETL/ELT processes using tools like Airflow, Luigi, or dbt to automate data workflows and transformations
</li></ul><ul><li>Experience with big data architectures and optimizing data pipelines
</li></ul><ul><li>Deep familiarity with SQL for data manipulation and querying
</li></ul><ul><li>Strong coding skills in Python, and at least one other language (Scala/Java)
</li></ul><ul><li>Hands-on experience with cloud-based data platforms (Azure/AWS/GCP)
</li></ul><ul><li>Strong analytical skills for working with large-scale unstructured datasets
</li></ul><ul><li>Ability to diagnose data issues, optimize performance, and communicate technical solutions effectively to both technical and non-technical stakeholders
</li></ul><ul><li>Educational qualifications: Bachelor&rsquo;s degree in Computer Science, Engineering, or related field required</li></ul></div></div>
<br><div><div>Responsibilities</div></div><div></div>
<br><div><div>Qualifications</div></div><div></div>
<br><div><div>About Us</div>
<div><div><b>About Us:<br>
</b></div><div></div><br>
<div>First Abu Dhabi Bank (FAB) is the largest bank in the UAE and one of the world's largest and safest financial institutions. We offer a comprehensive range of personal and private banking services, including credit cards, Islamic banking, investments, loans, and mortgages. Our commitment to excellence and innovation drives us to provide top-tier financial solutions to our clients.<br>
</div><div></div><br>
<div><b>Life at FAB:<br>
</b></div><div></div><br>
<div>Working at FAB means being part of a team of talented and passionate individuals with a shared vision to support the ambitions of our stakeholders to &quot;Grow Stronger.&quot; We embrace the needs of our customers across the globe with a sense of responsibility and confidence driven by extensive expertise that can only be delivered by an ambitious world-class organization<br>
</div><div></div><br>
<div><b>Career Development:<br>
</b></div><div></div><br>
<div>FAB offers unique career choices, a chance to innovate, craft solutions for the future, and express yourself in a performance-based culture that will unleash the best in you. Whether you are an experienced professional or just starting your career, FAB provides a range of learning and development initiatives to support all employees through training and skill development.<br>
</div><div></div><br>
<div><b>Our Values:<br>
</b></div><div></div><br>
<div>At FAB, we place our customers at the core of our activities, live our values each day in every way, celebrate achievements, and empower each other to deliver leading solutions. We have structured plans for the recruitment and career progression of Emirati talent to enable them to make a mark in the financial and banking sector both regionally and globaly that rewards your hard work and dedication.<br>
</div><div></div><br>
<div>Join our team and be part of a journey to shape the future of banking.</div></div></div><div></div>

Data Architect

Contango

<div>
 <strong>
  Contract duration:
 </strong>
 6 months (with a potential extension)
 <br/>
 <br/>
 <strong>
  Engagement Type:
 </strong>
 Full-time
 <br/>
 <br/>
 <strong>
  Start date:
 </strong>
 July 2026
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 Abu Dhabi (on-site)
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We are seeking an experienced Data Engineer to design, build, and operate scalable, secure, and reliable data pipelines and platforms that power analytics and AI solutions for companies in the UAE. The role is hands-on and client-facing, owning data solutions end-to-end &mdash; from architecture and development to production and hypercare &ndash; on cloud and on-premise.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and maintain scalable batch and streaming data pipelines (ETL/ELT) that move data reliably from source systems to analytics and AI workloads.
  </li>
  <li>
   Build and optimize data models, databases, data warehouses, and lakehouse architectures (e.g., Databricks, Microsoft SQL Server) for performance and cost.
  </li>
  <li>
   Develop and tune distributed processing jobs using Spark/PySpark, including cluster management and optimization.
  </li>
  <li>
   Ensure data quality and data governance across the full data lifecycle (collection, access, storage, transformation, retention).
  </li>
  <li>
   Productionize pipelines with CI/CD, orchestration (e.g., Airflow, Azure Data Factory), monitoring, and alerting.
  </li>
  <li>
   Build the data foundation for analytics and AI use cases, collaborating closely with Data Scientists and AI Engineers (e.g., feature engineering, RAG data processing).
  </li>
  <li>
   Translate client business requirements into data architecture decisions and communicate trade-offs to technical and non-technical stakeholders.
  </li>
  <li>
   Maintain technical documentation, data lineage, and delivery artifacts across Design, Build, UAT, Production &amp; Hypercare.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Candidate Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Demonstrated experience delivering AI solutions in an enterprise or client-facing/consulting environment.
  </li>
  <li>
   Prior experience at management consulting firms and/or Big Tech is an advantage.
  </li>
  <li>
   Strong programming in Python and SQL with solid software engineering fundamentals.
  </li>
  <li>
   Hands-on experience with Spark/PySpark and big-data processing at scale.
  </li>
  <li>
   Proven experience building production ETL/ELT pipelines.
  </li>
  <li>
   Practical knowledge of a major cloud data stack &mdash; Azure, AWS, or GCP.
  </li>
  <li>
   Experience with a modern data platform (Databricks, Snowflake, or equivalent).
  </li>
  <li>
   Familiarity with orchestration, CI/CD, and DevOps (e.g., Airflow, Git, Docker).
  </li>
  <li>
   Understanding of data warehousing concepts, data modeling, data governance, and security best practices.
  </li>
  <li>
   Experience with dashboard or frontend engineering is a plus.
  </li>
  <li>
   Strong collaboration and communication skills, with the ability to work directly with clients.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's or Master&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field.
  </li>
  <li>
   3&ndash;6 years of experience in data engineering, building and operating data pipelines at scale.
  </li>
  <li>
   Preferred certifications: cloud data certifications such as Azure Data Engineer, AWS Data Engineer, or Databricks Data Engineer.
  </li>
 </ul>
</div>


Data Engineer (6 months contract)

<div><p><b>Contract duration: </b>6 months (with a potential extension)<br>
<b>Engagement Type:</b> Full-time<br>
<b>Start date: </b>July 2026<br>
<b>Location:</b> Abu Dhabi (on-site)</p><p></p><p><b>
Role Overview</b></p><p>
We are seeking an experienced Data Engineer to design, build, and operate scalable, secure, and reliable data pipelines and platforms that power analytics and AI solutions for companies in the UAE. The role is hands-on and client-facing, owning data solutions end-to-end &mdash; from architecture and development to production and hypercare &ndash; on cloud and on-premise.<br>
<br>
<b>Key Responsibilities</b></p><ul><li><p>
Design, build, and maintain scalable batch and streaming data pipelines (ETL/ELT) that move data reliably from source systems to analytics and AI workloads.</p></li><li><p>
Build and optimize data models, databases, data warehouses, and lakehouse architectures (e.g., Databricks, Microsoft SQL Server) for performance and cost.</p></li><li><p>
Develop and tune distributed processing jobs using Spark/PySpark, including cluster management and optimization.</p></li><li><p>
Ensure data quality and data governance across the full data lifecycle (collection, access, storage, transformation, retention).</p></li><li><p>
Productionize pipelines with CI/CD, orchestration (e.g., Airflow, Azure Data Factory), monitoring, and alerting.</p></li><li><p>
Build the data foundation for analytics and AI use cases, collaborating closely with Data Scientists and AI Engineers (e.g., feature engineering, RAG data processing).</p></li><li><p>
Translate client business requirements into data architecture decisions and communicate trade-offs to technical and non-technical stakeholders.</p></li><li><p>
Maintain technical documentation, data lineage, and delivery artifacts across Design, Build, UAT, Production &amp; Hypercare.</p></li></ul><p><b><br>
Candidate Requirements</b></p><ul><li><p>
Demonstrated experience delivering AI solutions in an enterprise or client-facing/consulting environment.</p></li><li><p>
Prior experience at management consulting firms and/or Big Tech is an advantage.</p></li><li><p>
Strong programming in Python and SQL with solid software engineering fundamentals.</p></li><li><p>
Hands-on experience with Spark/PySpark and big-data processing at scale.</p></li><li><p>
Proven experience building production ETL/ELT pipelines.</p></li><li><p>
Practical knowledge of a major cloud data stack &mdash; Azure, AWS, or GCP.</p></li><li><p>
Experience with a modern data platform (Databricks, Snowflake, or equivalent).</p></li><li><p>
Familiarity with orchestration, CI/CD, and DevOps (e.g., Airflow, Git, Docker).</p></li><li><p>
Understanding of data warehousing concepts, data modeling, data governance, and security best practices.</p></li><li><p>
Experience with dashboard or frontend engineering is a plus.</p></li><li><p>
Strong collaboration and communication skills, with the ability to work directly with clients.</p></li></ul><p><b><br>
Qualifications</b></p><ul><li><p>
Bachelor's or Master&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field.</p></li><li><p>
3&ndash;6 years of experience in data engineering, building and operating data pipelines at scale.</p></li><li><p>
Preferred certifications: cloud data certifications such as Azure Data Engineer, AWS Data Engineer, or Databricks Data Engineer.</p></li></ul></div>

Birbal AI

<div>
 <p>
  The Data Engineer will be responsible for supporting data management, system integration, reporting data flows, and enterprise application data activities. The role requires hands-on experience in SQL, data pipelines, data extraction, transformation, APIs, CRM/Dataverse data structures, reporting datasets, and production support.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Key Responsibilities
 </p>
 <p>
  Develop, maintain, and optimize data pipelines and data integration workflows.
 </p>
 <p>
  Work with SQL databases, CRM/Dataverse, APIs, and enterprise application data sources.
 </p>
 <p>
  Support data extraction, transformation, loading, and reconciliation activities.
 </p>
 <p>
  Build and maintain datasets for dashboards, reports, and analytics.
 </p>
 <p>
  Troubleshoot data issues related to missing records, incorrect mappings, failed integrations, or report mismatches.
 </p>
 <p>
  Support integration between enterprise applications, portals, CRM systems, and reporting platforms.
 </p>
 <p>
  Work with Power BI datasets, SQL scripts, views, stored procedures, and data models.
 </p>
 <p>
  Support automation workflows using Power Automate or similar platforms.
 </p>
 <p>
  Coordinate with business users, application teams, QA teams, and data quality resources to resolve data issues.
 </p>
 <p>
  Prepare and maintain technical documentation for data flows, mappings, APIs, and transformation logic.
 </p>
 <p>
  Ensure data security, confidentiality, governance, and compliance requirements are followed.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Required Skills
 </p>
 <p>
  Strong SQL development and database knowledge.
 </p>
 <p>
  Experience in ETL/ELT, data pipelines, and data integration.
 </p>
 <p>
  Knowledge of CRM/Dataverse or similar enterprise application data models.
 </p>
 <p>
  Experience with Power BI datasets, reporting databases, or analytics platforms.
 </p>
 <p>
  Understanding of APIs, data exchange, and system integration.
 </p>
 <p>
  Good knowledge of data validation, data reconciliation, and data troubleshooting.
 </p>
 <p>
  Strong analytical, problem-solving, and communication skills.
 </p>
</div>


Data Engineer – SQL, Power BI & Dataverse

Tandem Interim

<div>
 <p>
  Hiring: Data Quality Developer
 </p>
 <p>
  <br/>
 </p>
 <p>
  📍 Abu Dhabi, UAE (Onsite)
 </p>
 <p>
  📅 12-Month Contract
 </p>
 <p>
  🏢 Management Consulting Firm
 </p>
 <p>
  <br/>
 </p>
 <p>
  A leading consulting firm is seeking a
  <strong>
   Data Quality Developer
  </strong>
  to support a large-scale government data transformation program in Abu Dhabi.
 </p>
 <p>
  This role focuses on designing, implementing, and automating data quality controls across source systems, ETL/ELT pipelines, and analytical platforms to ensure data is accurate, complete, consistent, and reliable.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Key Responsibilities
 </p>
 <ul>
  <li>
   Perform data profiling and analysis to identify quality issues across source systems.
  </li>
  <li>
   Develop automated validation checks across ETL/ELT pipelines.
  </li>
  <li>
   Validate schema changes, data types, constraints, and referential integrity.
  </li>
  <li>
   Detect and investigate anomalies, duplicates, missing values, and out-of-range data.
  </li>
  <li>
   Build reusable data quality frameworks using SQL, Python, or similar technologies.
  </li>
  <li>
   Implement automated reconciliation, regression testing, and validation processes.
  </li>
  <li>
   Monitor critical data pipelines and investigate data quality incidents.
  </li>
  <li>
   Conduct root cause analysis and work with engineering teams to resolve issues.
  </li>
  <li>
   Document validation logic, business rules, and data quality controls.
  </li>
  <li>
   Contribute to enterprise data quality standards, frameworks, and best practices.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Requirements
 </p>
 <ul>
  <li>
   5&ndash;7 years of experience in Data Quality, Data Engineering, Analytics Engineering, or related fields.
  </li>
  <li>
   Strong hands-on experience supporting production ETL/ELT environments.
  </li>
  <li>
   Experience developing automated data validation and quality controls.
  </li>
  <li>
   Advanced SQL skills for profiling, reconciliation, and validation.
  </li>
  <li>
   Experience with Python or other scripting languages.
  </li>
  <li>
   Familiarity with data warehouses, data lakes, and modern data platforms.
  </li>
  <li>
   Experience with workflow orchestration and scheduled pipelines.
  </li>
  <li>
   Strong troubleshooting, debugging, and problem-solving skills.
  </li>
  <li>
   Ability to work closely with Data Engineers, BI teams, and Analytics teams.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Nice to Have
 </p>
 <ul>
  <li>
   Experience with Data Quality tools and frameworks.
  </li>
  <li>
   Exposure to government or large-scale enterprise data environments.
  </li>
  <li>
   Experience with metadata management or data cataloging solutions.
  </li>
  <li>
   Knowledge of statistical and rule-based validation techniques.
  </li>
  <li>
   DAMA, CDMP, or Data Governance certifications.
  </li>
 </ul>
 <p>
 </p>
</div>


Data Quality Developer

DICETEK LLC

<div><p><b>Role requires 10+ years of experience.</b></p><ul><li>Must‑have skills include:</li><li>ETL Testing</li><li>Finance domain expertise</li><li>Strong SQL</li><li>Data profiling</li><li>BI report validation</li><li>No special or additional skill expectations beyond SQL + ETL + BI validation.</li><li>This is a Test Lead role.</li></ul><p><b>
Description:</b></p><p><b>
Role Summary:
</b></p><p>Lead end-to-end validation of complex finance data pipelines and reporting solutions.
</p><p>Ensure data integrity, accuracy, and completeness across ETL workflows, data warehouses, and regulatory/financial reporting systems.<br>
</p><p></p><br>
<p><b>Key Responsibilities</b>:
</p><p>Own test strategy, planning, and execution for ETL, data quality and finance reporting deliverables Validate data transformations, aggregations, reconciliations, and reporting accuracy across multiple source systems</p><p>
Define and implement test automation frameworks for data validation and regression testing Collaborate with data engineering, BI, finance, and business stakeholders to clarify requirements and resolve issues
</p><p>Lead defect triage, root-cause analysis, and continuous quality improvement Govern quality metrics, reporting, and controls for financial reporting compliance</p><p><b>
Skills &amp; Experience</b>:</p><p>
10+ years in data/ETL testing with finance domain experience (P&amp;L, GL, regulatory reporting)
</p><p>Strong SQL, data profiling, and BI report validation expertise
</p><p>Working knowledge of data warehousing, ETL tools, cloud data platforms
</p><p>Proven leadership in large, complex data programs with cross-functional teams</p></div>

Lead Data Quality Assurance (QA) Engineer

<div>
 <strong>
  Contract duration:
 </strong>
 6 months (with a potential extension)
 <br/>
 <br/>
 <strong>
  Engagement Type:
 </strong>
 Full-time
 <br/>
 <br/>
 <strong>
  Start date:
 </strong>
 July 2026
 <br/>
 <br/>
 <strong>
  Location:
 </strong>
 Abu Dhabi (on-site)
 <br/>
 <br/>
 <strong>
  About Contango
  <br/>
  <br/>
 </strong>
 Contango is the strategic partner for transformative growth and sustained success for the ADQ portfolio. Our team excels in providing comprehensive growth solutions that combine global best practices with local market expertise. We focus on long-term value creation, empowering our clients to achieve the full scale of their aspirations. As a trusted advisor to ADQ's portfolio companies, Contango helps CEOs drive strategic growth initiatives, navigate disruptive forces, and maximize long-term value creation.
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 As a Senior Data Scientist, you will independently work on specific data projects and be responsible for implementing analytical solutions. You will design, build, deploy, and support end-to-end Data &amp; AI solutions. You will translate complex business challenges into scalable, production-ready analytics and machine learning systems, collaborating closely with product, data engineering, and architecture stakeholders to deliver measurable impact.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Use Case Framing &amp; Solution Design
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Translate client business problems into end-to-end system architectures that combine Data, ML, and software components.
  </li>
  <li>
   Lead the design of scalable, modular AI solutions, defining services, interfaces, and data flows.
  </li>
  <li>
   Make explicit trade-offs across performance, cost, latency, and maintainability.
  </li>
  <li>
   Define success metrics, SLAs, and non-functional requirements (reliability, security, scalability).
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Engineering &amp; Feature Systems
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and implement robust data pipelines (batch and streaming) with strong guarantees on quality, lineage, and observability.
  </li>
  <li>
   Build and manage feature pipelines and feature stores, ensuring consistency between training and inference.
  </li>
  <li>
   Collaborate with platform teams to define data models, schemas, and storage strategies.
  </li>
  <li>
   Enforce standards for data validation, testing, and monitoring within production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Applied ML &amp; Production-Grade Development
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop ML solutions using production-quality code (Python/JS), following software engineering best practices.
  </li>
  <li>
   Structure codebases into maintainable, testable modules, with clear separation of concerns.
  </li>
  <li>
   Implement unit, integration, and end-to-end tests for data and ML components.
  </li>
  <li>
   Package models and logic into deployable services (APIs, microservices, batch jobs) using modern frameworks.
  </li>
  <li>
   Balance model sophistication with system performance, latency, and operational constraints.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  MLOps, DevOps &amp; Platform Integration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build and maintain CI/CD pipelines for ML systems, including automated testing, validation, and deployment.
  </li>
  <li>
   Containerize and deploy services using Docker, Kubernetes, and cloud-native tooling.
  </li>
  <li>
   Implement model versioning, experiment tracking, and artifact management.
  </li>
  <li>
   Design monitoring and observability systems (logs, metrics, alerts) for both data and model performance.
  </li>
  <li>
   Automate retraining, rollback, and release strategies to ensure system resilience.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  System Reliability, Scalability &amp; Security
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design systems for high availability, fault tolerance, and horizontal scalability.
  </li>
  <li>
   Optimize performance across data pipelines and inference services (latency, throughput, cost).
  </li>
  <li>
   Apply secure coding practices, access controls, and data protection standards.
  </li>
  <li>
   Manage technical debt and ensure long-term maintainability of production systems.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Documentation, Standards &amp; Engineering Excellence
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Produce developer-focused documentation (APIs, architecture diagrams, runbooks).
  </li>
  <li>
   Establish and enforce coding standards, review processes, and engineering best practices.
  </li>
  <li>
   Build reusable libraries, SDKs, and internal frameworks to accelerate delivery.
  </li>
  <li>
   Drive continuous improvement in engineering maturity, tooling, and delivery practices across the consultancy.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Experience And Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Prior experience at management consulting firms and/or Big Tech is an advantage.
  </li>
  <li>
   Client-serving experience is an advantage.
  </li>
  <li>
   5+ years of experience in data science or a related analytical field.
  </li>
  <li>
   5+ years delivering end-to-end analytics/ML solutions from problem framing through deployment and ongoing monitoring in production.
  </li>
  <li>
   Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, and security.
  </li>
  <li>
   Prior experience in developing AI solutions on public cloud services is an advantage.
  </li>
  <li>
   Bachelor&rsquo;s degree (Master&rsquo;s preferred) in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering).
  </li>
  <li>
   Technical Expertise:
  </li>
  <ul>
   <li>
    Coding &amp; data querying: Python (pandas/NumPy) and SQL; writing clean, testable code with Git.
   </li>
   <li>
    Statistics &amp; experimentation: Probability/statistics, hypothesis testing, regression, and A/B testing/experimental design.
   </li>
   <li>
    ML modelling: Feature engineering, model selection, cross-validation, metrics, and hyperparameter tuning (supervised/unsupervised).
   </li>
   <li>
    Data prep &amp; analysis: ETL/EDA, data cleaning, handling missing/outliers, and building insight narratives with visuals.
   </li>
  </ul>
 </ul>
</div>


Senior Data Scientist (6 months contract)

Explore 41+ Etl developer in Abu Dhabi this July. Find roles across top companies and apply now to boost your career.

41 etl developer jobs In Abu Dhabi

Data Architect

Data Engineer (6 months contract)

Data Engineer (6 months contract)

Data Engineer – SQL, Power BI & Dataverse

Data Quality Developer

Lead Data Quality Assurance (QA) Engineer

Senior Data Scientist (6 months contract)