High-Performance Data Architect

We are seeking an experienced and visionary leader to drive the design and implementation of scalable, high-performance data solutions that support Sales, Marketing, Manufacturing, Finance, and Engineering across a world-class organization.

The ideal candidate will serve as a technical leader and mentor, driving best practices in data engineering, architecture, and governance. They should be deeply curious about the evolving data landscape, passionate about innovation, and committed to enabling AI-powered business capabilities through high-quality, well-governed data.

• Architect and Design Complex Data Pipelines: Using Databricks and Azure Data Services, create scalable, high-performance data solutions that meet business needs.
• Lead Development of Scalable Data Solutions: Utilize Python, PySpark, and distributed computing frameworks to develop robust data solutions.
• Define and Enforce Data Quality Standards: Ensure data is timely, accurate, and complete by defining and enforcing data quality standards.
• Design and Maintain Enterprise-Grade Data Models: Use star and snowflake schemas to design and maintain enterprise-grade data models.
• Write and Review Advanced SQL: Write and review advanced SQL, including CTEs, aggregations, and complex joins.
• Collaborate with Cross-Functional Teams: Translate business needs into robust data solutions by collaborating with cross-functional teams.
• Champion Documentation, Metadata Management, and Data Governance: Promote documentation, metadata management, and data governance practices throughout the organization.
• Guide Power BI and Sigma Computing Dashboard Development: Guide the development of Power BI and Sigma Computing dashboards and semantic models.
• Integrate Data from Relational and NoSQL Sources: Integrate data from relational (Oracle, SQL Server, Postgres) and NoSQL (MongoDB) sources.
• Lead Integration Efforts with Informatica Cloud Platform: Architect and implement integration efforts with Informatica Cloud Platform, including Customer 360, Reference 360, and MDM SaaS.
• Architect Real-Time Data Ingestion: Architect and implement real-time data ingestion using Kafka, AWS SNS/SQS, and event-driven patterns.
• Mentor Junior Engineers: Mentor junior engineers, promote knowledge sharing, and foster a culture of technical excellence.

• Deep understanding of data engineering principles and technologies: Proven experience with data engineering tools and platforms, such as Databricks, Azure Data Services, Python, PySpark, and distributed computing frameworks.
• Strong programming skills: Proficiency in languages such as Python, Java, and SQL.
• Data modeling and architecture: Experience designing and implementing data models, including star and snowflake schemas.
• Database management: Knowledge of relational and NoSQL databases, including Oracle, SQL Server, Postgres, and MongoDB.
• Cloud platform experience: Familiarity with cloud-based platforms, such as AWS and Azure.
• Communication and collaboration: Excellent communication and collaboration skills, with experience working with cross-functional teams.

This role offers a unique opportunity to work with a world-class team, leveraging cutting-edge technologies to drive business growth and success. The successful candidate will have access to ongoing training and professional development opportunities, as well as a competitive compensation package.

As a leader in this field, you will have the opportunity to make a lasting impact on the organization's data strategy and operations. You will be part of a collaborative and dynamic team, working together to drive innovation and excellence in data engineering and architecture.