Teradata Data Architect

• We are seeking an experienced Teradata Data Architect to design and lead enterprise-scale data architecture, data warehousing, and Lakehouse solutions. The ideal candidate will have strong expertise in Teradata, modern Databricks architecture, data modelling, and large-scale data processing using PySpark. The role involves modernizing legacy data platforms, implementing scalable Lakehouse architectures, and establishing enterprise data governance and security standards.
• Design and implement enterprise data architecture across Teradata.
• Architect modern Lakehouse solutions using Databricks, Delta Lake, and cloud data platforms.
• Lead data warehouse modernization, migration, and integration initiatives from Teradata to Databricks.
• Design conceptual, logical, and physical data models for enterprise data warehouses and Lakehouse platforms.
• Develop and optimize data pipelines using PySpark, Spark SQL, SQL, and Databricks workflows.
• Implement enterprise data governance, data discovery, access controls, lineage, and metadata management using Unity Catalog.
• Define data ingestion, transformation, ETL/ELT, batch processing, and streaming architecture.
• Optimize Teradata SQL, Spark jobs, Delta Lake tables, query performance, and overall platform costs.
• Establish standards for data quality, security, scalability, reliability, and regulatory compliance.
• Collaborate with data engineers, business analysts, cloud architects, and business stakeholders to translate requirements into technical architecture.
• Lead architecture reviews, technical design decisions, proof of concepts, and best-practice implementation.

Requirements

• Strong hands-on experience in Teradata database architecture, enterprise data warehousing, and SQL performance tuning.
• Proven experience designing modern data architectures using Databricks and the Lakehouse paradigm.
• Strong knowledge of Databricks Lakehouse, Delta Lake, and Apache Spark architecture.
• Hands-on experience with PySpark, Spark SQL, and distributed data processing.
• Experience with Unity Catalog, including data governance, permissions, lineage, metadata, and access control.
• Strong expertise in data modelling, dimensional modelling, data integration, and ETL/ELT architecture.
• Experience designing scalable data pipelines, data transformation frameworks, and enterprise data platforms.
• Knowledge of data security, data quality, data lifecycle management, and architecture standards.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.