Global Practioner

Collibra

1d•$168,000 - $210,000

About The Position

Joining Collibra’s Global Practitioner team. Collibra is seeking an experienced and dynamic leader to join our Global Practitioner team with a focus on Data Quality. This role is central to ensuring our prospects and customers maximize their investment by providing guidance, strategic consulting, and proven best practices to build data quality programs that make data trustworthy at scale. If you are passionate about driving business value through reliable, high-quality data, we encourage you to apply.

Requirements

Minimum of 3 years of experience as a Data Quality Program Leader, Data Reliability/Governance Program Manager, or equivalent senior-level role.
Minimum of 2 years of direct, hands-on experience as a key Champion or Stakeholder of Collibra Data Quality & Observability.
Practical fluency in core data quality concepts, quality dimensions, rule design, DQ scoring, monitoring and alerting, data observability, and remediation workflows.
Proven ability to engage customers in a highly consultative manner, establishing immediate credibility and fostering long-term strategic relationships.
Exceptional presentation and facilitation skills, with the ability to command and influence a room of diverse stakeholders, from technical teams to executive leadership.
Superior written and verbal communication skills, capable of articulating complex concepts clearly and persuasively.
A bachelor’s degree or equivalent related working experience is required.
Demonstrated proficiency in leveraging AI tools (e.g., Claude, Gemini, ChatGPT, Copilot) to solve real-world business challenges, drive measurable outcomes, or streamline workflows.
Strong ability to discover and work with use cases to help customers implement solutions. This process requires reflective listening, capturing the essence of the problem, and offering a proposed solution.
Ability to read and write Structured Query Language (“SQL”) in the context of DQ rules.
Understanding of data outliers, patterns, duplicates, and valid values (ranges, etc.).
Understanding of the core data quality dimensions.
Ability to read and write data quality rule logic (e.g. comparing multiple columns in a single dataset, or even comparing multiple datasets).
Ability to leverage an existing SQL function library function for use by a DQ rule (eg. length(‘Collibra’))
Ability to invoke an existing REST API endpoint, and the basics of HTTP: GET, and POST.
Ability to work with boolean logic operators AND, OR, and NOT.
Basic ability to navigate a Linux operating system and filesystem (eg. cd, pwd, ls, etc.).

Nice To Haves

Ability to understand and explain how Apache Spark works with data, at a high level, is a plus (not required). This is for DQ “pull up.”
Ability to understand how Kubernetes (K8s) and Docker containers work is a plus (not required).
Ability to read and write Python code is a plus (not required).

Responsibilities

Provide practical, expert guidance to executive stakeholders and program leaders to define, build, and sustain high-value Data Quality programs, including operating models, ownership, and the business case for trusted data.
Advise customers on designing effective data quality rules, quality dimensions and scoring, monitoring and alerting, and data observability practices that catch issues before they reach the business.
Help customers establish issue detection, triage, and remediation workflows, connecting data quality findings to clear ownership, root-cause analysis, and measurable improvement over time.
Guide the integration of data quality into pipelines, data products, and governance workflows so reliability is built in rather than bolted on.
Design and lead high-impact customer workshops on topics including data quality strategy, use case prioritization, rule and metric design, roles and stewardship, and adoption.
Execute comprehensive Data Quality Maturity Assessments to benchmark customer capabilities and formulate clear, phased roadmaps for improvement.
Develop, curate, and share cutting-edge data quality best practices and compelling customer success stories across the Collibra ecosystem.