Data Governance Engineer

Job Description :

MONIX is looking for a proactive Data Governance to ensure data is accurate, trusted, and well-managed across the organization. This role partners with business stakeholders and technical teams to implement data governance standards, improve data quality, maintain data documentation and metadata, support compliance requirements, and embed governance practices into data processes to enable effective decision-making and business growth.

Key Tasks & Responsibilities:

• Act as the day-to-day point person for data governance activities, coordinating tasks and serving as the main contact for governance matters across teams.

• Translate data governance policies and standards into action items, and close gaps by building and maintaining the data inventory, metadata register, business glossary, and data lineage for critical data.

• Define and run data quality checks (rules, scorecards, issue logging) and drive issues to resolution.

• Maintain governance evidence and support audits, assessments, and remediation tracking.

• Coordinate with data owners and stewards across teams to keep ownership and documentation current.

• Partner with the Data Engineering team to embed governance (classification, metadata, access controls) into data pipelines and the data development workflow.

• Support the delivery of new initiatives and adjustments, enabling faster, cleaner launches with governance built in.

• Automate repetitive governance tasks (e.g. metadata capture, quality validation) and help improve data infrastructure and tooling where practical.

• Manage your work with a good degree of independence, and when a decision is needed, come prepared with options and a suggested way forward.

Qualifications:

• Bachelor's degree or higher in Computer Science, Information Systems, Data/Information Management, Engineering, Statistics, or a related field.

• 1–5 years of experience in data governance, data management, data quality, or data engineering.

• Able to read a policy or standard and turn it into practical, executable action items.

• Working SQL; Python for data processing and task automation.

• Understanding of core data governance concepts: metadata, data quality, lineage, classification, data ownership/stewardship.

• Comfortable working with Data Engineering teams on pipelines and data infrastructure.

• Detail-oriented and organized, comfortable owning registers, trackers, and documentation over time.

• Able to work with a good degree of independence, and comfortable coming to decisions with options and a suggested way forward.