Data Engineer - Data Quality
Summary
Build and maintain data-cleansing pipelines and quality checks using Python, SSIS, Microsoft Fabric, and Power BI to ensure accurate, reliable enterprise data for reporting and analytics.
Job Snapshot
Role: Data Engineer - Data Quality
Location: Abu Dhabi, United Arab Emirates
Industry: IT and Services
Function: Database Development-Administration
Job Type: Full-time
Role Context
The Data Engineer - Data Quality will help ensure that enterprise data remains accurate, consistent, complete, and reliable across reporting, analytics, governance, and operational systems. The role focuses on cleansing raw and inconsistent data, building quality checks, improving data pipelines, and working with cross-functional teams to define standards that support trusted decision‑making. By using Python Notebooks, SSIS, Microsoft Fabric, Power BI, and equivalent tools, the engineer will help create scalable data quality processes that reduce errors and improve business confidence in data.
Key Responsibilities
- Cleanse, transform, validate, and standardize data using Python Notebooks, SSIS, Microsoft Fabric builds, Power BI, and other data engineering tools.
- Develop and maintain data quality processes that monitor accuracy, completeness, consistency, duplication, validity, and reliability of data assets.
- Build data cleansing pipelines that support efficient data preparation for reporting, analytics, governance, and downstream applications.
- Collaborate with business users, data analysts, data governance teams, and technology teams to define practical data quality standards.
- Identify data issues, investigate root causes, and recommend corrective actions to improve data integrity.
- Create automated checks, validation rules, exception reports, and monitoring processes for recurring data quality problems.
- Optimize data transformation and cleansing workflows for better performance, scalability, and maintainability.
- Support data profiling activities to detect anomalies, missing values, format issues, duplicates, and inconsistent records.
- Work with Power BI and Microsoft Fabric environments to support clean data models, reliable dashboards, and trusted reporting outputs.
- Document data cleansing logic, quality rules, pipeline behavior, issue patterns, and remediation steps.
- Participate in quality assurance reviews to confirm that data outputs meet business expectations and technical standards.
- Support continuous improvement of data engineering practices by introducing better automation, controls, and reusable cleansing methods.
Ideal Profile
- Proven experience in data engineering with a strong focus on data cleansing, data quality, and quality assurance.
- Practical knowledge of Python Notebooks, SSIS, Microsoft Fabric, Power BI, and equivalent data engineering platforms.
- Strong understanding of data quality principles, data profiling, transformation logic, validation rules, and data integrity controls.
- Ability to design and optimize data cleansing pipelines for large or complex data sets.
- Experience working with structured data, reporting data, analytics data, and enterprise data sources.
- Strong problem‑solving skills with the ability to trace data issues from source systems through transformation layers.
- Good attention to detail with a methodical approach to testing, validation, and documentation.
- Ability to work independently while also collaborating with cross‑functional teams in a fast‑paced environment.
- Clear communication skills for explaining data issues, quality gaps, and improvement recommendations to both technical and business users.
- A continuous improvement mindset with interest in building cleaner, more reliable, and scalable data engineering processes.
Skills Set
- Data engineering
- Data cleansing
- Data quality
- Data quality assurance
- Python Notebooks
- SSIS
- Microsoft Fabric
- Fabric Builds
- Power BI
- Data transformation
- Data validation
- Data profiling
- Data integrity
- Data standardization
- Data quality rules
- Data pipelines
- ETL processes
- Data monitoring
- Exception reporting
- Data remediation
- Quality checks
- Data accuracy
- Data consistency
- Data reliability
- Root‑cause analysis
- Performance optimization
- Scalable data processing
- Cross‑functional collaboration
- Technical documentation
Why Join Us
This role is a strong opportunity for a data engineer who wants to work on high‑value data quality and data cleansing initiatives in Abu Dhabi's enterprise technology market. The position offers exposure to modern data engineering tools, Microsoft Fabric, Power BI, Python‑based workflows, SSIS pipelines, and business‑critical data improvement projects where clean and reliable information directly supports better reporting, stronger governance, and smarter decision‑making.
About the Company
Dicetek LLC is a technology services and consulting company supporting clients across the UAE and wider region with skilled professionals in data engineering, software development, business analysis, cybersecurity, cloud, DevOps, and digital transformation. The company works with organizations that need dependable technology talent to improve enterprise systems, strengthen data quality, and deliver scalable digital solutions for long‑term business growth.
Job Details
Country: United Arab Emirates
City: Abu Dhabi
Salary: 18,000 – 28,000
Gender: Any
Candidate Nationality: Any
Job Type: Full‑time