Formulate the enterprise-wide data strategy to align with long-term business objectives and forecast future technological requirements.
Design scalable data architectures that integrate heterogeneous data sources. Ensure all designs adhere strictly to enterprise security and compliance standards.
Author the policies that govern data access, retention, and sovereignty globally. Establish the enforcement mechanisms.
Implement rigorous data governance frameworks. Define ownership, stewardship, and quality metrics for data residing in disparate lakes.
Audit the current portfolio of data tools. Identify redundancies and execute plans to decommission inferior software, thereby reducing technical debt.
Analyze existing data silos. Engineer integration patterns that expose trapped data to the broader enterprise without compromising integrity.
Confront business leaders with technical realities. Articulate the cost of sprawl and the value of a unified data model.

Requirements

Minimum 12 years in enterprise technology or data, with at least 5 years dedicated to data architecture.
Data Warehousing Methodologies: Both TOGAF certification and demonstrated thought leadership in convincing executives to invest in the formalism of full data lifecycle specific to Data Warehousing engineering and governance.
Technical Leadership: Deep, hands-on expertise in building architecture and engineering practices around any leading Data Warehouse.
Database Strategy: Proven mastery in rationalizing complex estates containing disparate relational and non-relational database system including proven track record of operationalizing data governance in complex environments.
Leadership: Demonstrated ability to influence C-level executives and steer large organizations without direct HR authority.
Complex Rationalization: History of successfully merging multi-national or multi-line-of-business data estates during M&A activities or massive re-organizations.
Recent, hands on technical experience with any of the following: Snowflake, AWS, Informatica, dbt, Datahub, and Presto, Datahub/Acryl (Desired).
Master’s degree in a quantitative field strongly preferred (Desired).

Benefits

Competitive pay
Generous time off
Ample parental and wellness leave
Healthcare
Retirement savings program
Additional compensation and benefits (incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, paid time off)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

data strategydata architecturedata governance frameworksdata warehousing methodologiesdata integration patternsdata quality metricsdata access policiesdata retention policiesdata sovereigntytechnical debt reduction

Soft skills

technical leadershipinfluencing executivesarticulating technical realitiesstakeholder engagementorganizational steeringcommunication skillsstrategic thinkingproblem-solvingnegotiation skillschange management

Certifications

TOGAF certificationMaster's degree in quantitative field