Data Architect

PwC is hiring a Data Architect. Level rates it ; you can apply on PwC.

Level's read on this job

Level rates this role Little AI ●○○○: aI is not part of the work.
PwC mentions visa sponsorship in this posting.
Tools and skills the posting cites include Databricks.
Level lists 3,700+ other open roles at PwC.

AI in this role

Databricks

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Platform Engineering & Architecture

Management Level

Associate

Job Description & Summary

The Data Architect is responsible for designing, implementing, and managing the organization’s data architecture to ensure optimal data flow, storage, and accessibility. This role involves creating scalable and secure data models, integrating data from multiple sources, and ensuring compliance with data governance and security standards.

Data Architecture Responsibilities
• Design and deliver enterprise and solution data architectures that solve business problems and enable analytics, reporting, and regulatory outcomes.
• Define and govern data models, standards, and best practices across conceptual, logical, and physical layers.
• Lead data analysis activities, including source system analysis, data profiling, and source-to-target mapping definitions.
• Develop and review data models and canonical data definitions; assure model alignment to business capabilities and use cases.
• Establish and embed data governance and data quality practices, policies, and controls, including measurement, monitoring, and remediation.
• Partner with business stakeholders to translate requirements into scalable data solutions and roadmaps; articulate trade-offs and options.
• Oversee non-functional requirements (scalability, performance, security, reliability) and align architecture to target-state principles.
• Provide architecture oversight through delivery, ensuring traceability from requirements to design to implementation.
• Contribute to reference architectures and reusable patterns (ingestion, curation, access) to accelerate delivery.

Technical Skills
• Data analysis and profiling; source-to-target mapping; data modeling across conceptual, logical, and physical layers.
• ETL/ELT and integration patterns; batch and streaming data processing.
• Data warehousing approaches; relational and analytical data stores.
• Cloud technologies (MS Azure, Databricks, AWS, GCP); metadata and lineage; data quality management and controls.
• Strong knowledge of data modeling, ETL processes, and data warehousing.

#PwCSEACPH

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred: Bachelor Degree

Certifications (if blank, certifications not specified)

Required Skills

Amazon Web Services (AWS), Cloud Platform, Data Lake, Data Warehouse, Generative AI, Google Cloud Platform (GCP), Machine Learning (ML), Programming Languages, SQL Databases

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Communication, Competitive Advantage, Continuous Process Improvement, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Emotional Regulation, Empathy, Inclusion, Industry Trend Analysis, Intellectual Curiosity, Java (Programming Language), Market Development {+ 7 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

Government Clearance Required?

Yes

Job Posting End Date

How we rate this

Data Architect at PwC rates 15 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.