Senior Data Quality Engineer (4 Months Contract ) Onsite in UAE - Octopus by RTG
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Key skills for this role
About the Role
Robusta Studio seeks a Senior Databricks Data Quality Engineer for a 4-month contract in Abu Dhabi. The role involves designing and implementing enterprise-scale data quality frameworks on Databricks, including profiling, rule automation, and AI-assisted monitoring across 170+ datasets.
Key Skills for This Role
Responsibilities
- Configure and manage Databricks workspaces, compute clusters, PySpark notebooks, Delta Lake architecture, and Unity Catalog integrations
- Design scalable data quality processing frameworks across 170+ datasets and 1,346 prioritized Critical Data Elements (CDEs)
- Develop AI assisted profiling notebooks using PySpark to establish baseline data quality scores
- Assess data quality across six key dimensions: Completeness, Uniqueness, Validity, Consistency, Accuracy, Timeliness
- Design and build a scalable Data Quality Rule Factory using parameterized PySpark functions
- Enable automated deployment of over 6,700 data quality rules without manual rule by rule development
- Integrate data quality controls within Bronze, Silver, and Gold Delta Lake layers
- Implement quality gates that prevent data progression unless predefined thresholds are met
- Build automated data cleansing pipelines for standardization, deduplication, and schema harmonization
- Deploy MLflow managed machine learning models for anomaly detection, fuzzy duplicate detection, and exact duplicate identification
- Design failed record handling frameworks and quarantine Delta tables
- Build Delta Lake aggregation tables for data quality metrics and deliver KPIs to Power BI dashboards
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field
- 5+ years of experience in Data Engineering or Data Quality Engineering
- 3+ years of hands on experience with Databricks and PySpark
- Strong expertise in Delta Lake architecture and data pipeline development
- Experience with Unity Catalog implementation and governance
- Hands on experience with MLflow and machine learning deployment
- Strong SQL skills and data modeling expertise
- Experience building enterprise scale data quality frameworks
- Experience integrating Databricks with Power BI and Azure services
- Strong understanding of data governance, metadata management, and data quality dimensions
Full Job Posting
About The Role
- We are seeking an experienced Senior Databricks Data Quality Engineer to lead the design, implementation, and automation of enterprise scale data quality frameworks within a Databricks environment. The successful candidate will play a key role in establishing data quality controls, profiling framewo
- This role requires strong expertise in Databricks, PySpark, Delta Lake, MLflow, and modern data quality management practices.
Key Responsibilities
- Configure and manage Databricks workspaces, compute clusters, PySpark notebooks, Delta Lake architecture, and Unity Catalog integrations.
- Design scalable data quality processing frameworks across 170+ datasets and 1,346 prioritized Critical Data Elements (CDEs).
- Develop AI assisted profiling notebooks using PySpark to establish baseline data quality scores.
- Assess data quality across six key dimensions including: Completeness, Uniqueness, Validity, Consistency, Accuracy, Timeliness.
- Analyze null rates, duplicate records, invalid values, format violations, outliers, and schema drift.
- Design and build a scalable Data Quality Rule Factory using parameterized PySpark functions.
- Enable automated deployment of over 6,700 data quality rules without manual rule by rule development.
- Create reusable rule templates across datasets and data quality dimensions.
- Integrate data quality controls within Bronze, Silver, and Gold Delta Lake layers.
- Implement quality gates that prevent data progression unless predefined thresholds are met.
- Develop reusable Databricks Jobs for automated validation and monitoring.
- Build automated data cleansing pipelines for: Standardization, Deduplication, Schema harmonization.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
- 5+ years of experience in Data Engineering or Data Quality Engineering.
- 3+ years of hands on experience with Databricks and PySpark.
- Strong expertise in Delta Lake architecture and data pipeline development.
- Experience with Unity Catalog implementation and governance.
- Hands on experience with MLflow and machine learning deployment.
- Strong SQL skills and data modeling expertise.
- Experience building enterprise scale data quality frameworks.
- Experience integrating Databricks with Power BI and Azure services.
- Strong understanding of data governance, metadata management, and data quality dimensions.
Preferred Qualifications
- Microsoft Azure certifications.
- Databricks Certified Data Engineer Associate or Professional.
- Experience with enterprise data governance programs.
- Experience implementing AI assisted data quality and remediation solutions.
- Knowledge of Master Data Management (MDM) principles
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