Collibra Developer

Role & responsibilities

Data Governance & Metadata Management:

Hands-on experience with Collibra for data governance and metadata management.

Strong understanding of data lineage, data cataloging, and data stewardship practices.

Data Quality Management:

Comprehensive knowledge of data quality frameworks, processes, and best practices.

Expertise in data profiling and cleansing techniques to identify duplicates, missing values, and anomalies. •

SQL & ETL Development:

Advanced proficiency in SQL for complex queries, joins, aggregations, and performance optimization.

Strong understanding of ETL workflows, data warehousing concepts, and data flow architecture.

Performance Optimization:

Ability to tune queries and optimize ETL processes for large-scale datasets.

Scripting & Automation:

Proficiency in Python or Shell scripting

Preferred candidate profile

Data Quality Dimensions:

In-depth understanding of Accuracy, Completeness, Consistency, Timeliness, Uniqueness, and Validity.

Business Rules Implementation:

Ability to translate business requirements into data quality checks and validation rules.

Data Governance Principles:

Knowledge of policies, standards, and compliance frameworks such as GDPR and other regulatory requirements.

Root Cause Analysis:

Skilled in identifying and resolving data quality issues at source to prevent recurrence.

Documentation & Reporting:

Experience in creating dashboards, reports, and metrics to monitor and communicate data quality performance.

Domain Expertise:

Familiarity with retail industry-specific data flows, processes, and

best practices.