Data Engineer | Dicetek | Abu Dhabi
Summary
Data Engineer at Dicetek in Abu Dhabi designing, building, and scaling cloud data pipelines and warehouse architectures on-site. Core stack: Databricks, Azure Data Factory, Azure Data Lake, DeltaLake, PySpark, Python, SQL, and Kafka, with CI/CD and MLOps practices supporting AI/ML and analytics workloads. Full-time permanent role.
Position Summary
- Dicetek is seeking an accomplished Data Engineer to join our expanding technology team in Abu Dhabi.
- This full-time position requires a seasoned technical professional capable of designing, building, and scaling modern cloud data pipelines and data warehousing architectures.
- You will play a pivotal role in engineering robust ETL/ELT workflows, real-time data processing streams, and scalable storage solutions using Databricks and Azure data technologies.
- The ideal candidate brings comprehensive expertise in PySpark, Python, SQL, Azure Data Factory, DeltaLake, and enterprise data modeling.
- Operating on-site in Abu Dhabi, you will collaborate closely with data scientists, business analysts, and analytics teams to support high-performance AI/ML workloads.
- Dicetek provides a dynamic, globally connected environment where your data engineering expertise directly drives enterprise intelligence and digital transformation.
- We welcome driven data professionals who excel in pipeline optimization, data quality enforcement, and MLOps automation.
Detailed Job Description
- As a Data Engineer at Dicetek, your core responsibilities encompass end-to-end data pipeline development, data warehousing, and performance tuning.
- You will leverage Azure Data Factory, Databricks, and DeltaLake to build scalable ETL/ELT data ingestion and transformation workflows across distributed cloud environments.
- Utilizing Python and PySpark, you will process massive structured and unstructured datasets, implementing real-time data streaming solutions via Kafka.
- Your daily engineering duties involve designing dimensional data models, optimizing SQL queries, and ensuring high standards of data quality, security, and validation.
- You will collaborate proactively with Data Scientists to operationalize AI/ML models and support advanced analytics workloads through robust MLOps practices.
- Implementing continuous integration and continuous deployment (CI/CD) pipelines ensures automated, reliable data deployments across development and production stages.
- Troubleshooting pipeline bottlenecks, monitoring cloud resource utilization, and maintaining comprehensive technical documentation are essential to your success.
Key Responsibilities
- Design, develop, test, and maintain scalable ETL and ELT data pipelines for enterprise data platforms.
- Build robust data integration and transformation solutions utilizing Azure Data Factory, Databricks, and Azure Data Lake.
- Develop advanced data models, data warehouses, and real-time data processing solutions using Kafka and PySpark.
- Implement comprehensive data quality, validation, security governance, and performance optimization practices.
- Support AI/ML and advanced analytics workloads by collaborating directly with Data Scientists and business stakeholders.
- Implement CI/CD and MLOps practices for automated, reliable, and version-controlled data deployments.
- Process, clean, and transform complex datasets using Python, SQL, and DeltaLake architectures.
- Monitor data pipeline execution metrics, troubleshoot ingestion errors, and execute rapid performance tuning.
- Ensure strict adherence to cloud data security standards, data privacy, and governance compliance.
- Maintain up-to-date technical documentation, data lineage diagrams, and pipeline runbooks.
Required Qualifications & Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, or a related technical field.
- Strong, proven professional experience designing and maintaining cloud-based data engineering solutions.
- Extensive hands-on expertise with Databricks, Azure Data Factory, Azure Data Lake, and DeltaLake.
- Deep proficiency in PySpark, Python, and advanced SQL programming for data transformation.
- Solid practical experience with real-time data processing frameworks such as Apache Kafka.
- Demonstrated mastery in ETL/ELT development, data modeling, and enterprise data warehousing.
- Strong understanding of data quality assurance, validation techniques, and performance optimization.
- Familiarity with CI/CD pipelines, MLOps practices, and cloud data architecture principles.
- Legal eligibility and physical presence capability to work on-site in Abu Dhabi.
Nice-to-Have Skills
- Professional certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Developer.
- Prior experience working in financial services, telecommunications, or enterprise consulting environments.
- Familiarity with infrastructure-as-code (IaC) tools such as Terraform for cloud resource provisioning.
- Experience with containerization platforms (Docker/Kubernetes) for data workload orchestration.
- Knowledge of advanced data governance tools (e.g., Microsoft Purview, Apache Atlas).
Application Information
- Salary/Rate: Competitive Market Standard
- Deadline: Open / Immediate Hiring
- Notice Period: Immediate to 30 Days Preferred
- Contract Duration: Full-Time Permanent Position
Recruitment Pro Tip
Highlight your hands‑on experience with Databricks, PySpark, Azure Data Factory, and real-time Kafka streaming in your CV to immediately capture the recruiter’s attention.
Skills
- AI
- Analytics
- Automation
- Azure
- Azure Data Factory
- CI/CD
- Cloud
- Containerization
- Data Engineering
- Data Governance
- Data Ingestion
- Data Lake
- Data Lineage
- Data Modeling
- Data Pipelines
- Data Quality
- Data Warehousing
- Databricks
- Docker
- ELT
- ETL
- Infrastructure as Code
- Kafka
- Kubernetes
- Machine Learning
- MLOps
- PySpark
- Python
- SQL
- Terraform