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Tier-1 brand and mid-level data role increase applicant density despite some niche Dataiku/regulatory requirements.
Heavy financial-regulatory, ITESS control, and governance requirements limit cross-industry transferability.
Mandatory Dataiku/Python skills, SDLC/ITESS compliance, and regulated-finance experience make filtering stringent.
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Design, build, and maintain data quality infrastructure supporting Legal's regulatory reporting, governance, analytics, and AI objectives.
Develop and operate data quality pipelines using Dataiku, Python, and automation frameworks ensuring compliance with enterprise SDLC and ITESS standards.
Lead integration with enterprise data governance tools, maintain dashboards and monitoring systems, and support innovation initiatives in data quality engineering.
Strong proficiency with Dataiku including visual and code recipes, model deployment, and orchestration.
Experience with Python programming for data pipelines and dashboard backend development.
Bachelor’s degree required; Master’s preferred in Computer Science, Data Engineering, Information Systems, or related technical field.
Work Experience Required: Relevant experience in data engineering, data quality, or analytics engineering roles; Financial services or regulated environment experience preferred.
Experienced in developing scalable data quality solutions with strong SDLC, CI/CD, and IT controls knowledge within regulated sectors.
Skilled in cross-functional collaboration across legal, technology, data risk, and analytics teams to deliver compliant and robust data quality platforms.
Capable of managing multiple projects with disciplined engineering and proactive stakeholder communication in complex organizational environments.