AI & Data Solutions Architect

Role Overview

The Analytics Engineering Tech Lead will be responsible for helping drive the strategy, design, and delivery of scalable data products that enable business stakeholders to make data-informed decisions. This role sits at the intersection of data engineering and analytics, ensuring that robust, governed, and high-quality data is available across the organization. They will act as a technical leader and collaborator, working closely with engineering, product, and business teams to shape the enterprise data landscape.

Key Responsibilities

Collaborates with senior business and technology stakeholders to define MVP scopes and design data solutions aligned with enterprise architecture strategy.

Alongside with the lead team defines the architectural strategy for data analytics, visualization and activation, aligned with the company guideline.

Guides the development and maintenance of ELT / ETL pipelines using modern tools and frameworks (e.g., dbt, Airflow), ensuring scalability, reliability, and data quality.

Designs and maintains enterprise and solution-level data models, supporting both operational and analytical needs.

Provides technical leadership to analytics engineers and data engineers, promoting best practices, code standards, and agile workflows.

Facilitates collaboration across multidisciplinary teams, translating complex business requirements into sustainable data products.

Required Qualifications & Skills

Experience in data / analytics engineering, including leadership or tech lead responsibilities.

Understanding of cloud architecture, especially Google Cloud Platform (GCP), including BigQuery, Dataflow, Pub / Sub, and Cloud Composer.

Proficiency in SQL, dbt, and Python; experience with modern ELT / ETL development and data transformation best practices.

Solid understanding of data modeling techniques.

Experience with BI tools (e.g., Tableau, Looker, Power BI).

Experience leading technical teams and mentoring junior developers.

Excellent communication and stakeholder management skills; ability to explain technical concepts to non-technical audiences.

• Plus : Knowledge in Machine Learning and experience with AI deployment.

Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

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