Architect, Data Governance

Lovelytics•Arlington, VA

17d•$170,000 - $190,000•Remote

About The Position

Lovelytics is seeking a Data Governance Architect to develop and implement data and AI governance strategies for their clients. This role involves defining technical strategies, architecting data platforms, and guiding implementation teams. The architect will also collaborate with sales and account teams to scope projects, create proposals, and demonstrate the company's governance expertise. This position is open to remote candidates in the U.S. and Ontario, Canada, with the option to work from offices in Arlington, VA; Chicago, IL; New York, NY; or Toronto.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data governance with 4+ years in a client facing role, preferably in a professional services firm.
Mastery in data governance capabilities as defined by the DAMA-DMBOK.
Certified in governance toolsets such as Unity Catalog, Atlan, or Anomalo.
Expert knowledge of Databricks and Spark (required).
Experience creating proofs of concept, technical presales presentations, and pricing for engagements.
Strong client-facing communication skills with the ability to influence technical and executive stakeholders.
Familiarity with a tech stack of Google Workspace (email, tools), MacOS, Slack (internal comms), Atlassian.

Responsibilities

Formulating data and AI governance strategies aligned with business objectives and industry best practices.
Creating, socializing, and implementing data governance policies, procedures, and frameworks for clients while ensuring compliance.
Introducing emerging technologies and methodologies for completion of data governance tasks and capabilities.
Developing and executing data governance and/or AI Governance strategy that improved data discoverability, data quality, accessibility, usability, AI use case evaluation, and AI readiness.
Leading the successful migration of complex data architecture from on-premises to cloud environments.
Establishing and enforcing data governance practices resulting in improved data security and compliance.
Introducing containerization to the organization, enhancing scalability and deployment efficiency.
Mentoring engineers, reviewing architectures and code, and guiding teams through implementation.
Leading technical discovery, shaping solution architectures, responding to RFPs, and delivering demos and proofs of concept for data engineering engagements.
Creating technical blueprints and recommending tools, frameworks, and design patterns aligned to client needs.