Collibra Developer

Weekday AI (YC W21); Chennai District; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

Weekday AI (YC W21) is seeking a senior Data Governance and Quality professional to lead metadata, lineage, and quality programs across enterprise data assets.

You will drive governance policy, cataloging, profiling, and validation workflows, partnering with IT and business teams for scalable data quality improvements. This role targets regions across major Indian tech hubs and requires strong SQL/ETL and scripting capabilities.

Qualifications

• Must have hands-on data governance and metadata management experience.
• Strong knowledge of data quality frameworks and profiling practices.
• Proficiency in SQL for complex queries and ETL workflows.
• Experience in tuning ETL processes for large datasets.
• Automation scripting in Python or Shell for quality checks.

Responsibilities

• Ensure integrity, accuracy and compliance of enterprise data assets.
• Translate business rules into data quality checks and validations.
• Develop dashboards and metrics to monitor data quality performance.
• Collaborate on data lineage, cataloging and governance improvements.

Skills

Data Governance & Metadata Management

Data Quality Management

SQL & ETL Development

Performance Optimization

Scripting & Automation

Data Quality Dimensions

Business Rules Implementation

Data Governance Principles

Root Cause Analysis

Documentation & Reporting

Domain Expertise

Collibra

Tools

Collibra Data Governance Center

Metadata Management

Job description

Job Description

This role is for one of Weekday’s clients
Salary range: Rs 1500000 - Rs 3500000 (ie INR 15 - 35 LPA)

Min Experience: 6+ years
Location: Kolkata, Bangalore, Chennai
JobType: full-time

Desired Competencies (Technical/Behavioral Competency)

• Must-Have
  • Data Governance & Metadata Management:
    • o Hands-on experience with Collibra for data governance and metadata management.
    • o Strong understanding of data lineage, data cataloging, and data stewardship practices.
  • Data Quality Management:
    • o Comprehensive knowledge of data quality frameworks, processes, and best practices.
    • o Expertise in data profiling and cleansing techniques to identify duplicates, missing values, and anomalies.
  • SQL & ETL Development:
    • o Advanced proficiency in SQL for complex queries, joins, aggregations, and performance optimization.
    • o Strong understanding of ETL workflows, data warehousing concepts, and data flow architecture.
  • Performance Optimization:
    • o Ability to tune queries and optimize ETL processes for large-scale datasets.
  • Scripting & Automation:
    • o Proficiency in Python or Shell scripting for automating data quality checks and validation processes.
• Good-to-Have
  • Data Quality Dimensions:
    • o In-depth understanding of Accuracy, Completeness, Consistency, Timeliness, Uniqueness, and Validity.
    • o Business Rules Implementation:
      • o Ability to translate business requirements into data quality checks and validation rules.
    • Data Governance Principles:
      • o Knowledge of policies, standards, and compliance frameworks such as GDPR and other regulatory requirements.
    • Root Cause Analysis:
      • o Skilled in identifying and resolving data quality issues at source to prevent recurrence.
    • Documentation & Reporting:
      • o Experience in creating dashboards, reports, and metrics to monitor and communicate data quality performance.
    • Domain Expertise:
      • o Familiarity with retail industry-specific data flows, processes, and best practices.

Expectations from the Role

1 highly skilled professional with expertise in Data Governance, Data Quality, and Metadata Management to ensure the integrity, accuracy, and compliance of enterprise data assets. The ideal candidate will possess strong technical capabilities combined with a deep understanding of data governance principles and business processes within the retail domain.

Must-have skills

Collibra Data Governance Center, Metadata Management

Good-to-have skills

Data Lineage, data catalogin, data stewardship

Requirements