Teradata Data Architect

Unison Group; Malaysia; 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. The role requires strong expertise in Teradata, modern Databricks architectures, and large-scale data processing using PySpark.

You will drive modernization of legacy platforms, implement scalable Lakehouse architectures, and establish enterprise data governance and security standards through collaboration with data engineers, analysts,

Qualifications

• Strong hands-on Teradata database architecture experience.
• Proven design of modern data architectures using Databricks Lakehouse.
• Extensive knowledge of Delta Lake and Apache Spark architecture.
• Hands-on PySpark and distributed data processing.
• Experience with Unity Catalog governance, permissions, lineage, metadata, access control.
• Expertise in data modelling, dimensional modelling, data integration, ETL/ELT.

Responsibilities

• Design and lead enterprise-scale data architecture, data warehousing, and Lakehouse solutions.
• Architect modern Lakehouse solutions using Databricks, Delta Lake, and cloud platforms.
• Lead data warehouse modernization and migration from Teradata to Databricks.
• Define data ingestion, transformation, ETL/ELT, batch and streaming architectures.
• Develop and optimize data pipelines using PySpark and Spark SQL.
• Collaborate with engineers, analysts, cloud architects, and stakeholders.
• Lead architecture reviews, technical decisions, and proof-of-concepts.

Skills

Teradata architecture

Databricks Lakehouse

Delta Lake

Apache Spark

PySpark

SQL performance tuning

Data modelling

ETL/ELT architecture

Data governance

Unity Catalog

Cloud platforms (AWS/Azure/GCP)

Data security & compliance

Tools

Databricks

Unity Catalog

Delta Lake

Spark SQL

PySpark

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.

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.