Teradata Data Architect

Unison Group; Kuala Lumpur; On-site; MYR 180,000 - 360,000; Full time

Job summary

Unison Group is seeking an experienced Teradata Data Architect to design and lead enterprise-scale data architecture, data warehousing, and Lakehouse solutions in Kuala Lumpur. The role requires strong expertise in Teradata, Databricks, and PySpark, with a focus on modernizing legacy platforms and implementing governance standards.

You will architect end-to-end data solutions, guide migrations from Teradata to Databricks, and collaborate with engineers and business stakeholders to translate

Qualifications

• Strong hands-on experience in Teradata database architecture and enterprise data warehousing.
• Proven ability to design modern data architectures using Databricks and the Lakehouse paradigm.
• Expertise in data modelling, dimensional modelling, and ETL/ELT architecture.
• Experience with governance, security, lineage, and metadata management.

Responsibilities

• Design and lead enterprise data architecture across Teradata and Lakehouse platforms.
• Architect modern Lakehouse solutions with Databricks, Delta Lake, and cloud data platforms.
• Lead data warehouse modernization, migration, and Teradata-to-Databricks initiatives.
• Develop and optimize data pipelines using PySpark, Spark SQL, and Databricks workflows.
• Define ingestion, transformation, ETL/ELT, batch, and streaming architectures.
• Establish data quality, security, scalability, and regulatory compliance standards.

Skills

Teradata

Databricks

PySpark

SQL tuning

Data governance

Cloud platforms

Tools

Databricks

Delta Lake

Unity Catalog

Apache Spark

Spark SQL

Job description

• 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.

• 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.