Senior Data Architect

at  McAfee LLC

Have hands-on experience with six or more of the following:

• Design and implementation of logical and physical data models.
• Data modeling tools, such as Erwin or ER/Studio.
• Databricks / Spark.
• Lakehouse architecture and medallion data organization.
• ETL/ELT development, monitoring, pipelining and orchestration.
• Python/PySpark, Scala or similar programming language.
• Data quality guidelines and testing frameworks.
• Creating technical design documents and data flow diagrams.
• CI/CD pipelines.
• Agile sprints.
• Git and version control

We are seeking a seasoned analytical leader to join our Enterprise Data Platform team as a Senior Data Architect, reporting to the Capability Lead – Data Architecture. As a member of McAfee’s enterprise data architecture team, you will manage data platform architecture on the Databricks platform.

This role requires a deep understanding of:

• Data lakehouse modeling and design
• ETL/ELT design
• Dimensional and relational data modeling
• Data warehouse design
• Security and PII management

This is a Remote position located in Canada. We are only considering candidates located in Canada and are not providing relocation at this time.

About the role:

• Design and organize data platforms, including databases and data structures, data storage, access, loading, and pipeline design.
• Collaborate with data stewards and data engineers on solution design.
• Develop and maintain physical data models for the Databricks platform.
• Manage metadata in data catalog tools, such as Collibra.
• Ensure adherence to data curation standards and guidelines for medallion certification framework and required architecture.
• Ensure the platform and platform design meets required security and compliance guidelines including PII management.
• Provide oversight to data curation teams, ingestion engineers and data engineers, including code review and data model design review to ensure adherence to standards and best practices.

About you:

• Bring 6+ years of experience in data engineering, data modeling, and ETL/ELT.
• Have experience as a senior engineer, including conducting code reviews.

Have hands-on experience with six or more of the following:

• Design and implementation of logical and physical data models.
• Data modeling tools, such as Erwin or ER/Studio.
• Databricks / Spark.
• Lakehouse architecture and medallion data organization.
• ETL/ELT development, monitoring, pipelining and orchestration.
• Python/PySpark, Scala or similar programming language.
• Data quality guidelines and testing frameworks.
• Creating technical design documents and data flow diagrams.
• CI/CD pipelines.
• Agile sprints.
• Git and version control.