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data engineer

Dicetek LLC

<div>
 Role Overview
 
 
 We are seeking a highly skilled and motivated Data Engineer with 5&ndash;7 years of experience to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong expertise in SQL, Databricks, Confluent (Kafka), Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS), with a solid understanding of banking domain processes and regulatory considerations. This role involves working closely with cross-functional teams to enable data-driven decision-making across critical banking functions.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, develop, and maintain robust, scalable data pipelines using Azure Data Factory (ADF) and Databricks
 </li>
 <li>
 Implement batch and real-time data ingestion frameworks leveraging Confluent Kafka
 </li>
 <li>
 Build and optimize data models, transformations, and ETL/ELT pipelines using SQL and Spark
 </li>
 <li>
 Develop and manage data storage solutions in Azure Data Lake Storage (ADLS)
 </li>
 <li>
 Ensure high data quality, integrity, and governance standards
 </li>
 <li>
 Support data integration across systems including core banking and CRM
 </li>
 <li>
 Optimize performance of large-scale datasets
 </li>
 <li>
 Collaborate with stakeholders to translate requirements into solutions
 </li>
 <li>
 Ensure compliance with banking regulations and data privacy
 </li>
 <li>
 Troubleshoot production issues
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Strong expertise in SQL (complex queries, tuning, modeling)
 </li>
 <li>
 Hands-on experience with Databricks, Spark, PySpark
 </li>
 <li>
 Experience with Confluent Kafka and event-driven architecture
 </li>
 <li>
 Experience with Azure Data Factory (ADF)
 </li>
 <li>
 Experience with Azure Data Lake Storage (ADLS)
 </li>
 <li>
 Understanding of data warehousing concepts
 </li>
 <li>
 Familiarity with CI/CD and DevOps for data platforms
 
 
 </li>
 </ul>
 
 Domain Knowledge (Preferred)
 
 
 
 <ul>
 <li>
 Experience in banking or financial services
 </li>
 <li>
 Understanding of core banking systems
 </li>
 <li>
 Knowledge of payments, lending, wealth management
 </li>
 <li>
 Awareness of regulatory frameworks (KYC, AML)
 
 
 </li>
 </ul>
 Soft Skills
 
 
 <ul>
 <li>
 Strong analytical and problem-solving skills
 </li>
 <li>
 Excellent communication and stakeholder engagement
 </li>
 <li>
 Ability to work in fast-paced environments
 </li>
 <li>
 Strong ownership and collaboration mindset
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in relevant field
 </li>
 <li>
 Azure/Data engineering certifications preferred
 
 
 </li>
 </ul>
 Good to Have
 
 
 <ul>
 <li>
 Experience with Python or Scala
 </li>
 <li>
 Exposure to data governance tools
 </li>
 <li>
 Knowledge of APIs and microservices
 </li>
 <li>
 Experience with BI tools like Power BI
 </li>
 </ul>
</div>

Data Engineer

Heidelberg Materials Trading

<div>
 
 Heidelberg Materials Trading is the international trading arm of Heidelberg Materials, one of the world&rsquo;s largest building materials companies, handling overseas drybulk product exports and imports across global markets. We are looking for a talented individual to join our IT team in our Dubai Office as:
 
 
 
 
 
 Data Engineer
 
 
 
 
 
 
 
 About the Role:
 
 
 
 This role sits at the centre of a greenfield transformation initiative, where we are replacing legacy reporting workflows with a modern, Microsoft first cloud data platform. You will work directly with IT and business stakeholders to connect our front office (Salesforce) and back office (JD Edwards ERP) systems into a unified analytics layer powering business critical Power BI dashboards. The role requires a hands on technical developer who builds, and owns data pipelines end-to-end, and can operate pragmatically within a Microsoft Fabric&ndash;oriented environment while proposing justified alternatives when needed.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Lead the migration of reporting from QlikSense to Power BI, ensuring accurate replication of existing logic, KPIs, and reporting workflows.
 </li>
 <li>
 Design, build, and maintain scalable Azure SQL&ndash;based data pipelines to support analytics, reporting, and operational decision making.
 </li>
 <li>
 Build and optimise Power BI data models, reusable datasets, and semantic layers following best practice modelling principles.
 </li>
 <li>
 Integrate data from JD Edwards (ERP), Salesforce (CRM), and other business systems, ensuring accuracy, consistency, and reliability across the reporting lifecycle.
 </li>
 <li>
 Reverse engineer manual Excel-based workflows and translate them into automated SQL or Python based pipelines to improve efficiency and reliability.
 </li>
 <li>
 Implement data validation, quality checks, monitoring, and performance optimisation across the data platform and reporting layers.
 </li>
 <li>
 Deliver Power BI training for business users and create documentation, dashboards, and best practice materials.
 </li>
 <li>
 Work closely with cross-functional teams to understand business requirements and translate them into scalable, maintainable data and reporting solutions.
 </li>
 <li>
 Contribute to data governance, security standards, and consistent documentation practices.
 </li>
 <li>
 Support UAT cycles, phased go lives, and iterative enhancements to reporting processes.
 </li>
 </ul>
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Engineering, Information Systems, or a related field.
 </li>
 <li>
 Minimum 3 years of hands‑on experience in data engineering or data platform development. - Minimum 6 years for senior consideration.
 </li>
 <li>
 Strong SQL skills with experience working on relational databases and transformation logic.
 </li>
 <li>
 Hands‑on experience with Power BI (DAX, data modelling, row‑level security, performance optimisation).
 </li>
 <li>
 Experience developing ETL/ELT pipelines using Azure Data Factory, Azure Synapse, or Microsoft Fabric (experience with at least one is required).
 </li>
 <li>
 Experience integrating ERP or CRM systems such as JD Edwards, SAP, or Salesforce, with a strong advantage for candidates familiar with these architectures.
 </li>
 <li>
 Solid understanding of transactional vs analytical modelling and modern data warehousing approaches.
 </li>
 <li>
 Comfortable operating as a hands‑on builder, capable of developing, testing, and shipping data pipelines independently.
 </li>
 <li>
 Strong communication skills with the ability to translate technical detail into clear business language.
 </li>
 <li>
 Able to work within a Microsoft‑first environment while recommending alternative tools when supported by a clear business case.
 </li>
 <li>
 Exposure to Microsoft Power Platform (Power Automate, Power Apps) is an advantage.
 </li>
 <li>
 Experience in trading, logistics, or supply chain environments is beneficial.
 </li>
 <li>
 Familiarity with Azure‑based cloud data architectures is preferred.
 </li>
 </ul>
 
 
 
 
 
 
 We thank all applicants for their interest, but only shortlisted candidates will be contacted.
 
 
 
 
 All applications will be kept strictly confidential.
 
 
</div>

Maaloomatiia Academy

<div>
 
 Job Title
 
 
 
 
 Cloudera Data Engineer
 
 
 
 
 Job Scope
 
 
 
 We are seeking an experienced
 
 Cloudera Data Engineer
 
 with strong hands-on expertise in
 
 Cloudera CDP, Hadoop, Spark, Hive, and HDFS
 
 . The ideal candidate will be responsible for building and maintaining big data pipelines, optimizing data workflows, and supporting production environments to ensure reliability and performance.
 
 
 
 Main Duties And Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain big data pipelines using Cloudera CDP components.
 </li>
 <li>
 Develop and optimize ETL/ELT workflows using Spark, Hive, and Hadoop ecosystems.
 </li>
 <li>
 Manage and maintain HDFS storage, ensuring high availability and performance.
 </li>
 <li>
 Perform production support activities, including issue resolution, monitoring, and performance tuning.
 </li>
 <li>
 Work with data scientists, analysts, and other engineering teams to support data-driven initiatives.
 </li>
 <li>
 Ensure data governance, security, and compliance across big data environments.
 </li>
 <li>
 Troubleshoot cluster-level issues related to resource utilization, scheduling, and configuration.
 </li>
 <li>
 Participate in solution design, architecture discussions, and technical documentation.
 
 
 
 </li>
 </ul>
 
 Position Requirements
 
 
 
 <ul>
 <li>
 Strong hands-on experience with Cloudera CDP.
 </li>
 <li>
 Proficiency in Hadoop ecosystem: HDFS, YARN, MapReduce, Hive, Impala.
 </li>
 <li>
 Strong experience working with Apache Spark (PySpark or Scala preferred).
 </li>
 <li>
 Solid understanding of distributed systems and big data architecture.
 </li>
 <li>
 Experience with production support and troubleshooting in big data environments.
 </li>
 <li>
 Strong SQL skills and experience optimizing large-scale queries.
 </li>
 <li>
 Familiarity with Linux, shell scripting, and automation tools.
 </li>
 <li>
 Experience with version control (Git) and CI/CD workflows is a plus.
 
 
 
 </li>
 </ul>
 
 Education
 
 
 
 Bachelor's degree in Computer Science or any other related field
 
 
 
 Experience
 
 
 
 <ul>
 <li>
 Experience with cloud platforms (AWS, Azure, GCP) for big data workloads.
 </li>
 <li>
 Exposure to Kafka, NiFi, Oozie, or similar data orchestration tools.
 </li>
 <li>
 Knowledge of Docker, Kubernetes, or containerized environments.
 </li>
 <li>
 Understanding of security, encryption, and data governance concepts.
 </li>
 </ul>
</div>

Cloudera Data Engineer

GSSTech Group

<div>We are seeking an experienced Data Engineer with strong expertise in Python, Microservices Architecture, Data Transformation, and Backend Engineering to join our Data Engineering team. The ideal candidate will be responsible for designing and developing scalable backend services, data processing frameworks, RESTful APIs, and data transformation pipelines that support enterprise data-driven applications.
This role requires strong hands-on experience with Python-based web frameworks, database technologies, ETL pipelines, microservices, API security, and modern software engineering practices. Candidates should have experience building production-grade applications with a focus on scalability, reliability, security, and performance. 
Requirements 
Key Responsibilities<ul><li>Design, develop, and maintain scalable backend applications and web frameworks using Python.</li><li>Build robust RESTful APIs and microservices to serve enterprise datasets and business applications.</li><li>Develop and optimize data transformation pipelines to process, clean, enrich, and prepare data for analytics and business consumption.</li><li>Design and implement scalable data access layers integrating multiple relational and NoSQL databases.</li><li>Collaborate with frontend developers to integrate user-facing components with backend services.</li><li>Ensure applications are secure, highly available, performant, and maintainable.</li><li>Design and maintain database schemas and data models aligned with business requirements.</li><li>Implement ETL processes for extracting, transforming, and loading large-scale datasets.</li><li>Optimize database performance, query execution, and data retrieval mechanisms.</li><li>Troubleshoot production issues and implement scalable solutions for long-term platform stability.</li><li>Participate in code reviews, testing activities, technical design discussions, and engineering best practices.</li><li>Work closely with business stakeholders, architects, and engineering teams within Agile delivery environments.</li></ul>
Required Technical Skills
Python Development<ul><li>Strong hands-on experience in Core Python development.</li><li>Expertise in building backend services and APIs using Python.</li><li>Strong understanding of object-oriented programming principles and software design patterns.</li><li>Experience writing clean, reusable, maintainable, and production-quality code.</li></ul>
Web Frameworks &amp; API Development
Strong experience with one or more Python frameworks including:<ul><li>FastAPI</li><li>Flask</li><li>Django</li><li>Pyramid</li></ul>
Experience with:<ul><li>RESTful API design and development</li><li>API versioning and documentation</li><li>Routing and middleware implementation</li><li>Authentication and authorization</li><li>Framework testing and debugging</li></ul>
Microservices Architecture<ul><li>Strong experience designing and developing microservices-based applications.</li><li>Deep understanding of distributed systems architecture.</li><li>Experience building scalable and resilient service-oriented platforms.</li><li>Knowledge of service communication patterns and API orchestration.</li><li>Experience handling concurrent requests and high-volume transaction processing.</li></ul>
Asynchronous Programming<ul><li>Strong understanding of asyncio and asynchronous programming concepts.</li><li>Experience handling concurrent connections and non-blocking operations.</li><li>Knowledge of performance optimization for I/O-intensive applications.</li></ul>
Security &amp; API Protection<ul><li>Strong understanding of API and microservices security best practices.</li><li>Experience implementing:</li></ul><ul><li>
OAuth 2.0</li><li>
JWT Authentication</li><li>
API Gateway integrations</li><li>
Encryption and secure communication protocols 
<ul><li>Experience implementing authentication, authorization, and access control mechanisms.</li></ul></li></ul>
Database &amp; ORM Expertise<ul><li>Strong experience with relational and NoSQL databases.</li><li>Experience designing database schemas and optimizing database performance.</li><li>Strong proficiency with:</li></ul><ul><li>
SQL</li><li>
PostgreSQL</li><li>
MySQL</li><li>
MongoDB</li><li>
Redis</li></ul>
Hands-on experience with ORMs including:<ul><li>SQLAlchemy</li><li>Django ORM</li></ul>
Ability to:<ul><li>Define models</li><li>Perform CRUD operations</li><li>Write optimized queries</li><li>Handle transactions</li><li>Manage database migrations</li></ul>
Data Engineering &amp; Transformation<ul><li>Experience building and maintaining ETL pipelines.</li><li>Strong understanding of data transformation, enrichment, aggregation, and cleansing techniques.</li><li>Experience ensuring data quality, consistency, and integrity.</li><li>Ability to support analytical and data-driven applications through scalable processing frameworks.</li></ul>
DevOps &amp; CI/CD<ul><li>Experience building and maintaining CI/CD pipelines.</li><li>Experience deploying and supporting production-grade applications.</li><li>Understanding of infrastructure automation and modern software delivery practices.</li><li>Experience with release management and deployment workflows.</li></ul>
Big Data &amp; Data Technologies
Exposure to technologies such as:<ul><li>Hadoop</li><li>Apache Spark</li><li>Apache Kafka</li></ul>
Understanding of:<ul><li>Data Warehousing concepts</li><li>Distributed data processing</li><li>Enterprise data architectures</li></ul>
Version Control &amp; Development Practices<ul><li>Strong experience with Git version control.</li><li>Experience with:</li></ul><ul><li>
Branching strategies</li><li>
Code reviews</li><li>
Pull Requests</li><li>
Merge conflict resolution</li><li>
Collaborative development workflows</li></ul>
Testing &amp; Debugging<ul><li>Experience with:</li></ul><ul><li>
Unit Testing</li><li>
Integration Testing</li><li>
Logging</li><li>
Monitoring</li><li>
Performance Troubleshooting</li><li>
Production Support</li></ul>
Nice to Have<ul><li>Experience with AWS, Azure, or GCP.</li><li>Experience with Docker and Kubernetes.</li><li>Exposure to cloud-native architectures.</li><li>Knowledge of data governance, compliance, privacy, and security standards.</li><li>Experience supporting large-scale enterprise data platforms.</li></ul>
Required Competencies<ul><li>Strong analytical and problem-solving skills.</li><li>Excellent communication and stakeholder management capabilities.</li><li>Strong collaboration and teamwork skills.</li><li>Ability to work effectively in Agile/Scrum environments.</li><li>Strong ownership mindset with attention to detail.</li><li>Ability to document solutions and communicate technical concepts clearly.</li></ul>
Education
Bachelor&rsquo;s Degree in Computer Science, Information Technology, Engineering, Data Engineering, or a related field.</div>

Data Engineer - Python & Microservices

Datamatics Global Services Ltd

<div>Job Description &ndash; Data Quality Engineer (Databricks) &ndash; x 4 Positions 
Location: Abudhabi - UAE - Onsite 
Open to Relocate 
Duration: 6 months ( Extendable to One Year) 
Experience: 5 to 7 Years 
Project start date is 1st July - Immediate joiners will be preferred 
 
Role Overview 
The Data Quality Engineer will be responsible for designing, implementing, and operating ADC's enterprise data quality framework within the Databricks platform. The role will deliver automated profiling, quality rule execution, cleansing, monitoring, remediation support, and quality reporting capabilities across 170 datasets and 1,346 prioritised Critical Data Elements (CDEs). 
Working closely with Data Modellers, Data Catalogue Specialists, business data owners, and platform engineers, the Data Quality Engineer will establish scalable and reusable quality controls that improve trust, accuracy, completeness, consistency, timeliness, validity, and uniqueness across ADC's data estate. 
Key Responsibilities 
Databricks Platform Configuration and Administration<ul><li>
Configure and manage the Databricks environment supporting enterprise data quality operations.</li><li>
Establish and maintain:<ul><li>
Compute clusters.</li><li>
PySpark notebook frameworks.</li><li>
Delta Lake storage structures.</li><li>
Unity Catalog integration.</li></ul></li><li>
Optimise platform performance for large-scale profiling and rule execution across all in-scope datasets and CDEs.</li><li>
Implement development, testing, and production deployment standards for data quality assets.</li></ul>
Data Profiling and Quality Assessment<ul><li>
Design and develop AI-assisted profiling notebooks using PySpark.</li><li>
Perform baseline data quality assessments across the six quality dimensions:<ul><li>
Completeness.</li><li>
Accuracy.</li><li>
Consistency.</li><li>
Validity.</li><li>
Timeliness.</li><li>
Uniqueness.</li></ul></li><li>
Capture and analyse:<ul><li>
Null value rates.</li><li>
Duplicate records.</li><li>
Invalid values.</li><li>
Format violations.</li><li>
Outliers.</li><li>
Schema drift.</li></ul></li><li>
Produce quality profiling outputs for all prioritised CDEs and datasets.</li></ul>
Data Quality Rule Factory Development<ul><li>
Design and implement a reusable Data Quality Rule Factory.</li><li>
Build parameterised PySpark-based rule templates capable of supporting large-scale rule deployment.</li><li>
Enable automated generation and management of approximately 6,730 data quality rules without manual rule-by-rule development.</li><li>
Ensure rules are reusable, configurable, and maintainable across multiple datasets and domains.</li></ul>
Data Quality Controls and Pipeline Integration<ul><li>
Deploy quality rules as reusable Databricks Jobs integrated into Delta Lake processing pipelines.</li><li>
Embed quality controls within Bronze, Silver, and Gold processing stages.</li><li>
Implement automated quality gates preventing data progression where defined thresholds are not met.</li><li>
Maintain rule traceability and execution history for audit and governance purposes.</li></ul>
Data Cleansing and Quality Improvement<ul><li>
Develop automated remediation and cleansing pipelines using PySpark.</li><li>
Implement:<ul><li>
Standardisation routines.</li><li>
Data enrichment processes.</li><li>
Deduplication logic.</li><li>
Schema harmonisation controls.</li></ul></li><li>
Deploy machine learning models managed through MLflow for:<ul><li>
Anomaly detection.</li><li>
Exact duplicate detection.</li><li>
Fuzzy matching and duplicate identification.</li></ul></li><li>
Ensure all AI and ML recommendations are explainable, auditable, and routed through human-in-the-loop validation processes where required.</li></ul>
Exception Management and Reprocessing<ul><li>
Design and manage exception handling processes for failed quality records.</li><li>
Implement quarantine Delta Lake tables serving as the Failed Record Register.</li><li>
Capture and maintain:<ul><li>
Failure reason.</li><li>
Associated CDE.</li><li>
Rule reference.</li><li>
Processing timestamp.</li><li>
Resolution status.</li></ul></li><li>
Develop reprocessing workflows to support correction and controlled re-ingestion of remediated records.</li></ul>
Data Quality Metrics and Reporting<ul><li>
Develop Delta Lake metric aggregation structures supporting enterprise quality reporting.</li><li>
Calculate and publish:<ul><li>
Data Quality Index (DQI) scores.</li><li>
Dimension-level quality metrics.</li><li>
Rule pass/fail rates.</li><li>
Dataset compliance scores.</li><li>
SLA adherence indicators.</li></ul></li><li>
Provide curated outputs to support Power BI quality dashboards and executive reporting.</li></ul>
Monitoring, Alerting and Predictive Quality Management<ul><li>
Configure automated quality monitoring and alerting mechanisms.</li><li>
Implement threshold-based notifications using:<ul><li>
Databricks SQL Alerts.</li><li>
Azure Monitor integrations.</li></ul></li><li>
Develop predictive risk scoring models to identify datasets at risk of future quality degradation.</li><li>
Support proactive quality management and operational intervention activities.</li></ul>
Root Cause Analysis and Remediation Support<ul><li>
Apply Databricks machine learning and pattern analysis techniques to profiling and rule execution outputs.</li><li>
Support AI-assisted root cause analysis across established remediation categories.</li><li>
Identify recurring quality issues, systemic defects, and process breakdowns.</li><li>
Produce prioritised remediation datasets for business and operational stakeholders.</li><li>
Export remediation outputs to Power BI and Excel to support:<ul><li>
Remediation Tiering Matrix.</li><li>
Prioritisation Scoring Models.</li><li>
Governance reporting processes.</li></ul></li></ul>
Governance, Compliance and Stakeholder Engagement<ul><li>
Collaborate with Data Modellers and Data Catalogue Specialists to ensure quality controls align with authoritative data definitions and metadata standards.</li><li>
Support DDA and DGE governance processes by producing required quality artefacts and evidence.</li><li>
Maintain documentation, version control, and audit trails for all quality assets, rules, models, and processes.</li><li>
Participate in quality reviews, governance forums, and stakeholder workshops.</li></ul>
Required Skills and Experience<ul><li>
Strong experience designing and implementing enterprise Data Quality frameworks.</li><li>
Advanced Databricks engineering experience.</li><li>
Strong PySpark development skills.</li><li>
Experience with:<ul><li>
Delta Lake.</li><li>
Unity Catalog.</li><li>
Databricks Workflows and Jobs.</li><li>
Databricks SQL.</li></ul></li><li>
Experience building scalable data validation and quality rule frameworks.</li><li>
Knowledge of machine learning techniques for anomaly detection and data quality monitoring.</li><li>
Experience using MLflow for model management and deployment.</li><li>
Strong understanding of data governance, metadata management, and data lifecycle processes.</li><li>
Experience integrating data quality metrics into reporting platforms such as Power BI.</li><li>
Knowledge of cloud-based data engineering and modern lakehouse architectures.</li></ul>
Deliverables<ul><li>
Configured Databricks Data Quality environment.</li><li>
Enterprise Data Quality Rule Factory.</li><li>
AI-assisted profiling notebooks and baseline assessment outputs.</li><li>
Automated data quality validation and gating processes.</li><li>
Data cleansing and remediation pipelines.</li><li>
Failed Record Register and reprocessing workflows.</li><li>
Data Quality metric aggregation tables.</li><li>
DQI reporting feeds and dashboard datasets.</li><li>
Predictive quality monitoring and alerting solutions.</li><li>
Root Cause Analysis and remediation support datasets.</li><li>
Governance, audit, and compliance artefacts supporting DDA and DGE reviews.</li></ul>
dmGrkjT88v</div>

Data Quality Engineer (Databricks)

Systematic

Data and Solutions Engineer - Defence
 Abu Dhabi, UAE
 
About the Role
 Join our UAE Defence Services team and help transform complex military data into actionable insights that support mission-critical decision-making. You will work at the intersection of data engineering, Artificial Intelligence (AI) including agentic, and system integration to deliver operational capabilities across land, maritime, and joint environments.
 
Working closely with Defence customers, operators, and internal teams, you will design, implement, and support datadriven solutions within Systematic’s SitaWare ecosystem, contributing directly to real-world operational effectiveness.
 
Responsibilities
 
Data Integration & Engineering: Ingest, process, and integrate data from multiple sources into unified workflows
 Data Transformation & Pipelines: Design and manage pipelines using low/no-code tools, and business logic
 AI & Agentic Capabilities: Integrate AI services, including agentic workflows, to automate data processing
 System Integration: Configure and integrate systems to enable data exchange across complex architectures
 Visualisation & Reporting: Deliver dashboards, reports, and searchable datasets for operational use
 Solution Delivery: Support end-to-end delivery of mission-critical C4I solutions within scope, time, and quality
 Deployment & Support: Configure, deploy, and provide lifecycle support for operational systems
 Stakeholder Engagement: Engage users and stakeholders to capture requirements, drive solutions and adoption
 Training & Enablement: Train customers on data and AI tools to ensure effective operational use
 Business Development Support: Support proposals, solution scoping, and capture activities, including technical inputs, estimates, and development of demonstrations and PoCs
 
Required Skills & Experience
 
Technical
 
Experience in data engineering, system integration, or similar roles
 Familiarity with data integration tools (e.g., Node-RED, Apache NiFi)
 Experience with APIs, JSON/XML, and data processing
 Exposure to cloud platforms (AWS/Azure)
 Understanding of AI/ML services, models and agentic AI concepts
 
Professional Experience
 
Customer-facing or consultancy experience working with complex stakeholders
 Experience delivering solutions in Defence, security, or government environments
 Experience working in multi-domain operational contexts (advantage)
 
Soft Skills
 
Strong problem-solving and analytical skills
 Excellent communication and stakeholder engagement capabilities
 Ability to work independently and within multidisciplinary teams
 Professional presence with Defence customers
 
Education
 
Bachelor’s or Master’s degree in Computer Science, Data Science, IT, or related field
 
Additional Requirements
 
Fluent in English; Arabic is a strong advantage
 Eligible for UAE security clearance
 Willingness to travel within the region and to HQ as required
 
Why Join Us?
 
Work on mission-critical Defence systems with real-world impact
 Be part of a high-performing, multidisciplinary team
 Engage directly with end users and decision-makers
 Contribute to cutting-edge capabilities spanning data, AI, and simulation
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Get in touch
 
Greta Renner
 
Talent Acquisition Partner
 
.buttontext707a3bac96aae82e a{ border: 1px solid transparent; } .buttontext707a3bac96aae82e a: focus{ border: 1px dashed #1d1d1c !important; outline: none !important; }
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Location: 
Abu Dhabi, Abu Dhabi, AE
 
#job-location.job-location-inline { display: inline; }
 Business Unit: Defence
 Division: Defence Service Delivery
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 Get to know us
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 More than software
 Our business

Data & Solutions Engineer

KAYALI

<div>Who We Are
Fueled by passion, KAYALI was founded in 2018 by beauty mogul and fragrance fanatic, Mona Kattan. Translating to &lsquo;my imagination&rsquo; in Arabic, KAYALI provides a modern fragrance experience inspired by Mona&rsquo;s rich Middle Eastern heritage and the art of layering scents to help you create your mood; where sharing scents is a ritual and smelling good is both an act of goodwill and self-love. Mona collaborates with some of the world&rsquo;s most renowned perfumers and sources the finest ingredients to create unique juices that are infinitely memorable, long-lasting, and cruelty-free. Each luxurious fragrance is an ode to true craftsmanship and tells a special story, from the addictive notes to the multi-faceted jeweled bottles. 
Our Mission
To make everyone feel like the diamond they are! To build a global community of fragrance lovers through the power of scent and by providing them with the most innovative &amp; luxurious fragrances, education and sharing our Middle Eastern fragrance rituals with the world. 
Summary
Introduction of a new role to provide expertise across data warehousing platforms including Azure Data Bricks and Power BI along with all the necessary integrations. The BI Engineer will be responsible for supporting, implementing and maintaining data warehouse Pipelines and Reports to streamline business process. 
RESPONSIBILITIES:
Data Platform &amp; Architecture<ul><li>
Manage a scalable modern Data platform leveraging the Azure ecosystem, including Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and Azure Data Lake Storage.
</li><li>Design and implement Lakehouse architecture using Medallion (Bronze, Silver, Gold) patterns with Delta Lake to ensure data reliability, scalability, and performance with knowledge of Delta Lake and ACID-compliant data architectures
</li><li>Apply data modelling techniques (dimensional modelling, star/snowflake schemas) to support both operational and analytical use cases.</li></ul>
Data Engineering &amp; Pipelines<ul><li>
Develop and maintain robust, high-performance data pipelines using cloud-native technologies (Databricks, PySpark, Lakehouse Workflows) to support ingestion, transformation, and curation of large-scale datasets.
</li><li>Knowledge in identifying and resolving complex data discrepancies across multi-stage ETL/ELT pipelines, with a focus on root cause analysis (RCA) of failures, data skew, and late-arriving data etc.
</li><li>Build and optimize end-to-end data integration frameworks, including ingestion from relational databases, flat files, and third-party REST APIs (handling authentication, pagination, and incremental loads).
</li><li>Troubleshoot and resolve complex data pipeline failures, performance bottlenecks, and data inconsistencies, performing root cause analysis in production environments.</li></ul>
Business Intelligence &amp; Power BI<ul><li>
Design, develop, and optimize Power BI datasets, reports, and dashboards, applying best practices in data modelling, DAX, and performance tuning.
</li><li>High-level proficiency in performance tuning and semantic model debugging, specifically using tools like DAX Studio and Tabular Editor to isolate issues within the Filter Context, Row Context, and complex relationship cardinalities.
</li><li>Strategic ability to troubleshoot data issues and investigate Gateway connectivity failures, Direct Query latency issues, and visual-level calculation errors to ensuring report accuracy and faster response times for executive stakeholders.</li></ul>
Data Integration &amp; Consumption<ul><li>
Manage the integration of data platforms with Power BI, ensuring efficient data models and seamless data consumption for reporting and analytics.</li></ul>
Data Governance &amp; Security<ul><li>
Implement and manage data security frameworks, including role-based access control (RBAC), Row-Level Security, and governance using Unity Catalog or equivalent tools.</li></ul>
DevOps, CI/CD &amp; Deployment<ul><li>
Knowledge in CI/CD pipelines using Azure DevOps or GitHub Actions to enable automated, reliable, and consistent deployment of data solutions.</li></ul>
Performance Optimization &amp; Cost Management<ul><li>
Monitor and optimize data platform performance and cloud resource utilization, identifying cost optimization opportunities and ensuring efficient workload execution.</li></ul>
Data Quality &amp; Reliability<ul><li>
Implement data quality, validation, and monitoring frameworks to ensure accuracy, consistency, and reliability of data assets.</li></ul>
Stakeholder Collaboration &amp; Delivery<ul><li>
Collaborate with cross-functional teams including business stakeholders, analysts, and engineers to translate business requirements into scalable technical solutions.</li></ul> 

Requirements 
<ul><li>
 Minimum 5+ years in both Reporting and Data engineering domain, with at least 3+ years focused on Azure based data platforms mainly Power BI and Azure Databricks.</li><li>
 Comprehensive knowledge of the Azure Data Stack and Strong hands-on experience with Azure Databricks, Azure Data Lake Storage, Synapse, ADF and open-source cloud native tools.</li><li>
 Extensive experience in Power BI, including Dataset design and optimization, Report and dashboard development using calculated measures, DAX etc.</li><li>
Knowledge of performance tuning techniques (Query optimization, Import vs Direct Query, aggregations etc).</li><li>
Proficiency in SQL, PySpark, Python</li><li>
 Solid understanding on Data modelling techniques.</li><li>
 Effective problem-solving skills backed by strong people skills.</li><li>
 Excellent oral and written communication skills.</li></ul> 

Benefits 
<ul><li>
Premium Medical/Dental/Vision coverage</li><li>
Find your Magic Days</li><li>
Volunteer Day</li><li>
Birthday Leave</li><li>
Egg Freezing Benefits</li><li>
Employee discounts on all Kayali products</li><li>
Quarterly product gifting</li></ul> 
Kayali is committed to building diverse and inclusive teams and upholding an equal employment workplace that is free from discrimination. We hire stellar individuals regardless of their race, color, ancestry, religion, gender identity, national origin, sexual orientation, age, marital status, medical conditions, disability, or veteran status. If you need reasonable accommodations at any point in the application or interview process, please let us know.</div>

BI Engineer

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