Enterprise Architect

Twilio

2d•Remote

About The Position

This position is needed to transform our data ecosystem by designing and implementing a unified, governed data architecture across the company. This role is accountable for the technical rationalization of disparate data lakes, ensuring rigorous governance, and compelling cross-functional teams to adopt standardized, centralized data tooling. The Enterprise Architect responsible for the Enterprise Data Domain defines and executes the data strategy, determining the future state of our data ecosystem and bears accountability for its long-term viability.

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 mulit-line-of-business data estates during M&A activities or massive re-organizations.

Nice To Haves

Recent, hands on technical experience with any of the following: Snowflake, AWS, Informatica, dbt, Datahub, and Presto, Datahub/Acryl
Master’s degree in a quantitative field strongly preferred

Responsibilities

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.