# Collibra Data Lineage Engineer at Cygnify

> Onsite · Singapore · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3Acygnify%3A60809089-ea4b-40b6-8b7b-a0b026bf2147 (read 2026-11-12).

## Facts (observed)

- Company: [Cygnify](https://alderhq.app/companies/cygnify)
- Location text: Singapore
- Where it can be done from (inferred): Onsite · Singapore (evidence: "Location: Singapore")
- Posted: 2026-08-15 (89 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/cygnify/60809089-ea4b-40b6-8b7b-a0b026bf2147
- Skills listed (inferred): AWS, GCP, Azure, Airflow, Snowflake, dbt, SQL

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Singapore, n 19): p25 SGD 70k, median SGD 165k, p75 SGD 250k

## Description (the employer's text)

The Engineer will work closely with the Japanese Bank’s DMO / Data Governance Team, Data Office, DATA FSI Delivery leadership, and technical teams across Data, Integration, and Core Banking.

### Key Responsibilities

1. Collibra Implementation & Configuration:

• Develop, configure, and deploy data lineage workflows in Collibra (Technical & Business Lineage).

• Implement Collibra Data Catalog, Business Glossary, and custom domains/models.

• Configure Collibra Operating Model, communities, domains, roles, responsibilities.

• Build and optimise Collibra Workflows using BPMN and Collibra Workflow Designer.

2. Metadata & Lineage Integration

• Connect Collibra with enterprise systems:

• ETL/ELT Tools: Informatica, Talend, dbt, Airflow

• Data Lake / DWH: Snowflake, Databricks, Redshift, Oracle

• Core Banking Systems: CASA, Trade, Treasury, Payments, Channels

• Develop automated metadata ingestion pipelines (API, JDBC, custom scripts).

• Map and trace end-to-end lineage from source → transformation → consumption systems.

3. Data Governance & Regulatory Alignment

• Work with the Japanese Bank’s DMO on MAS-aligned data governance requirements (MAS 610/649, BCBS 239).

• Support creation and maintenance of Business Glossary, Data Dictionary, and ownership models:

• Data Owners

• Data Stewards

• Technical Owners

• Perform metadata quality checks and lineage validation.

4. Stakeholder & Delivery Management

• Engage with the Japanese Bank’s Data Governance, Compliance, Risk, and Technology teams.

• Provide technical SME guidance, defect remediation, and enhancement support.

• Prepare weekly progress reports, risks, issues, and present to the bank’s DMO / Delivery Lead.

• Contribute to DATA delivery governance with FSI Delivery Head.

### Required Skills & Experience

1. Technical Skills

• 3–6 years hands-on experience with Collibra (Catalog, Data Lineage, Glossary, Workflow).

• Strong understanding of:

• Metadata models & governance frameworks

• Collibra DGC concepts

• Custom lineage creation

• Integration via REST API, Edge, Lineage Harvesting tools

• Experience in mapping lineage for financial data flows (preferred).

• Proficiency in SQL and metadata extraction from databases & ETL pipelines.

• Knowledge of Cloud platforms (AWS / Azure / GCP) is a plus.

2. Domain Knowledge

• Functional understanding of Banking & FSI systems: CASA, Loan, Trade, Treasury, GL, Payments, Channels.

• Familiarity with MAS regulatory reporting, risk controls, or Data Governance programs.

3. Soft Skills

• Clear communication with senior stakeholders.

• Strong documentation and reporting capability.

• Ability to work independently under strict timelines.

• Positive, client-focused mindset; protects NTT’s reputation.

4. Certifications (Good to Have)

• Collibra Ranger / Collibra Steward / Collibra Workflow Engineer.

• Data Governance certifications (DAMA, DCAM).

• Cloud Architect or Data Engineering certification.

---
Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Acygnify%3A60809089-ea4b-40b6-8b7b-a0b026bf2147 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.