Principal Data Architect

We are hiring for "Principal Data Architect" at Virtusa.
Please share your updated CV along with below details

** Candidates with notice period more than 15 days need not apply

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* Current CTC -
* Expected CTC -
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Email : [email protected]

Position summary

The Senior Data Architect (P3) is a strong individual contributor responsible for designing and

implementing data models and architecture patterns across Wiley's Enterprise Data platform.

You will work closely with Principal architects, data engineers, and software engineers to deliver well-

modeled, governed data solutionsbuilding deep data modeling and cloud architecture expertise while

contributing to the standards that shape our platform.

Key responsibilities

• Design and implement conceptual, logical, and physical data models spanning transactional,

analytical, and lakehouse environments.

• Design and build data architecture solutions on Google Cloud Platform (GCP).
• Contribute to defining data governance, cataloging, and lineage standards.
• Apply data modeling best practices across relational, dimensional, and analytical schemas.
• Write and review Python and SQL to prototype, validate, and optimize data solutions.
• Collaborate with Data Engineering and Software Engineering teams to ensure data architecture

aligns with platform requirements.

• Participate in architectural reviews and provide input on complex data design decisions.
• Document data models, architecture decisions, and standards for broader engineering teams.
• Mentor junior data engineers on data modeling practices.

Required qualifications

• 4+ years of experience in data architecture, data modeling, or data engineering roles.
• Strong experience with data modeling: conceptual, logical, and physical modeling across relational,

dimensional, and analytical schemas.

• Strong experience with SQL for complex data manipulation and optimization.

• Strong experience with Python for prototyping and automation.

• Experience designing and implementing data solutions on Google Cloud Platform (GCP).

• Understanding of data warehousing, data lakes, and lakehouse architecture patterns.

• Experience contributing to data governance, cataloging, and lineage practices.

• Experience collaborating with engineering and business stakeholders on data requirements.

• Strong communication skills, with the ability to document and present data models and design

decisions.

Preferred qualifications

• Experience with modern data storage and open table formats, such as Parquet and Iceberg.
• Experience with data modeling tools such as Erwin, ER/Studio, TOAD Data Modeler, or DBML.
• Experience with dbt Core for transformation modeling.
• Experience with streaming or event-driven architectures, such as Kafka.
• Experience with data catalog and governance tooling.
• Experience in academic publishing, research, or education sectors.

Regards,
Pallavi Tapase