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Technical lead collibra

Costessey
Infoplus Technologies UK Ltd
Posted: 8h ago
Offer description

The Role

Role: TECHNICAL LEAD COLLIBRA

Location: Norwich, UK

Contract

Inside IR35


Responsibilities

Solution Architecture & Design

* Lead the design and implementation of Collibra-based data governance solutions, including:
o Data Catalog
o Business Glossary
o Policy & Standards
o Data Quality integration
o Operating models (roles, responsibilities, stewardships)
* Define Collibra architecture, metadata models, custom domains, and asset types.
* Create reusable frameworks for metadata ingestion, lineage, and governance workflows.

Collibra Configuration & Development

* Configure Collibra components, including:
o Custom asset models
o Attribute definitions
o Relations and hierarchies
o Workflows (BPMN-based)
o Data quality dashboards & certification workflows
* Develop and maintain Collibra REST APIs, Connect integrations, and catalog crawlers.
* Implement metadata onboarding processes and automated connectors to cloud/on-prem data platforms.

Data Governance & Data Quality Leadership

* Collaborate with data governance councils, data stewards, and business SMEs to define:
o Data standards
o Business glossary terms
o Data ownership & stewardship models
o Data quality rules, SLAs, and data issue management workflows
* Ensure alignment with enterprise data governance frameworks and compliance requirements.

Integration & Metadata Lineage

* Implement automated metadata ingestion from:
o Data lakes
o ETL tools (Glue, Informatica, Talend, IICS)
o Warehouses (Redshift, Snowflake, BigQuery)
o BI tools (Power BI, Tableau)
o Streaming sources (Kafka)
* Build lineage diagrams across ETL pipelines, APIs, datasets, and downstream consumption layers.
* Ensure metadata completeness, accuracy, and operational SLAs.


Your Profile

Essential skills/knowledge/experience:

* Data lakes
* ETL tools (Glue, Informatica, Talend, IICS)
* Warehouses (Redshift, Snowflake, BigQuery)
* BI tools (Power BI, Tableau)
* Streaming sources (Kafka)
* Build lineage diagrams across ETL pipelines, APIs, datasets, and downstream consumption layers.
* Ensure metadata completeness, accuracy, and operational SLAs.
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