Teradata Data Architect

<ul>
<li>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.</li>
<li>Design and implement enterprise data architecture across Teradata.</li>
<li>Architect modern Lakehouse solutions using Databricks, Delta Lake, and cloud data platforms.</li>
<li>Lead data warehouse modernization, migration, and integration initiatives from Teradata to Databricks.</li>
<li>Design conceptual, logical, and physical data models for enterprise data warehouses and Lakehouse platforms.</li>
<li>Develop and optimize data pipelines using PySpark, Spark SQL, SQL, and Databricks workflows.</li>
<li>Implement enterprise data governance, data discovery, access controls, lineage, and metadata management using Unity Catalog.</li>
<li>Define data ingestion, transformation, ETL/ELT, batch processing, and streaming architecture.</li>
<li>Optimize Teradata SQL, Spark jobs, Delta Lake tables, query performance, and overall platform costs.</li>
<li>Establish standards for data quality, security, scalability, reliability, and regulatory compliance.</li>
<li>Collaborate with data engineers, business analysts, cloud architects, and business stakeholders to translate requirements into technical architecture.</li>
<li>Lead architecture reviews, technical design decisions, proof of concepts, and best-practice implementation.</li>
</ul><h2>Requirements</h2><ul>
<li>Strong hands-on experience in<strong>Teradata database architecture,</strong>enterprise data warehousing, and SQL performance tuning.</li>
<li>Proven experience designing modern data architectures using Databricks and the Lakehouse paradigm.</li>
<li>Strong knowledge of<strong>Databricks Lakehouse, Delta Lake, and Apache Spark</strong>architecture.</li>
<li>Hands-on experience with<strong>PySpark, Spark SQL, and distributed data processing</strong>.</li>
<li>Experience with<strong>Unity Catalog</strong>, including data governance, permissions, lineage, metadata, and access control.</li>
<li>Strong expertise in data modelling, dimensional modelling, data integration, and ETL/ELT architecture.</li>
<li>Experience designing scalable data pipelines, data transformation frameworks, and enterprise data platforms.</li>
<li>Knowledge of data security, data quality, data lifecycle management, and architecture standards.</li>
<li>Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.</li>
</ul>