Collibra Engineer

Job Title: Collibra Data Quality & Data Intelligence Platform (DIP) Engineer

Location:

Bangalore (preferred). If not, can consider remote candidates out of India. Experience:

5+ Years

Role Overview : We are seeking an experienced

Collibra Data Quality & Data Intelligence Platform (DIP) Engineer

to support critical data quality initiatives for financial KPI reporting and governance. The ideal candidate will be hands-on in profiling large data sets, creating DQ rules, managing Collibra DIP workflows, and integrating quality frameworks to ensure data accuracy, consistency, and reliability across business functions.

Key Responsibilities Perform

comprehensive data profiling

on large and complex datasets to identify trends, patterns, and outliers. Configure and implement

data quality rules

in Collibra DQ to detect anomalies and enforce data standards. Schedule and manage

DQ jobs

to ensure continuous monitoring and timely issue detection. Analyze data profiling outputs to improve the trustworthiness of financial KPIs and reports. Develop and execute

custom SQL queries

for profiling, validation, and integration activities. Leverage

Collibra DIP features

for end-to-end data intelligence, cataloging, and lineage mapping. Collaborate with data governance, reporting, and business teams to

enforce DQ guardrails

and ensure compliance with organizational standards. Integrate

DQ and DIP solutions

within existing data pipelines and enterprise ecosystems. Document processes, configurations, and standards to ensure auditability and reproducibility.

Required Skills & Competencies Hands-on expertise

with Collibra DQ and Collibra DIP. Strong

SQL proficiency

for data analysis and rule configuration. Certified Collibra Ranger

preferred. Deep understanding of data profiling, pattern detection, and anomaly identification. Strong analytical thinking and

problem-solving mindset

. Excellent communication and documentation skills.

Preferred Qualifications Prior experience in Retail or Financial KPI reporting environments. Exposure to cloud-based data ecosystems (GCP, AWS, or Azure). Understanding of data governance principles and business impact of DQ.