Data Architect - Banking

Unison Group; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Unison Group is seeking a Data Architect with 10+ years in data, including 4+ years in banking, and hands-on data engineering experience. You will design enterprise data platforms across data warehouse, data lake and lakehouse architectures, and lead architecture reviews with governance and regulatory focus.

The role requires expertise in Teradata, Hadoop/Spark ecosystems, SQL, and data integration technologies, with strong emphasis on lineage, data quality and semantic layers.

Qualifications

• 10+ years in data, including 4+ years in banking
• Hands-on data engineering background
• Experience with data platform design inside large banks
• Familiarity with BCBS 239 standards for lineage, reconciliation and audit
• Knowledge of data architecture and modelling techniques
• Experience with data lakes, warehouses, lakehouse and data fabrics
• Understanding of data governance and metadata frameworks
• Experience with streaming/integration tooling like Kafka and Spark

Responsibilities

• Run design authority forums and review engineers' designs and code
• Write design specifications that pass architecture, audit and regulatory review

Skills

Data platform design

Banking data models

BCBS 239 compliance

Data architecture

Data modelling

Historical data design

Data-as-a-service patterns

Metadata & data quality

Streaming data processing

Data governance

Tools

Teradata

Hadoop

Cloudera

Spark

Python

R

SQL

Hive

Impala

HBase

Pig

Hue

Iceberg

Trino

Kafka

Informatica

Talend

Denodo

Snowflake

Databricks

Kubernetes

Job description

• Data platform design inside tier-1 or large regional banks

We are looking for a Data Architect with 10+ years in data, including 4+ years in banking and a hands-on data engineering background.

Must-have Skills

Banking and domain

• Data platform design inside tier-1 or large regional banks
• Banking data models (Teradata FSLDM or equivalent) across customer, account, payments and AML/CFT subject areas
• Financial crime or regulatory data marts built to BCBS 239 standards for lineage, reconciliation and audit

Data architecture

• Enterprise data warehouse, data lake and Lakehouse architecture; Data Mesh and Data Fabric concepts
• Data modelling: dimensional, 3NF and Data Vault; semantic layers and data products
• Historical data design: snapshots, SCD Type 2, bi-temporal models and large multi-grain backfills
• Data-as-a-service patterns across batch and API delivery, with lineage, observability and SLA monitoring
• Metadata, business glossary, lineage and data quality frameworks

Data engineering (hands-on)

• ETL/ELT development, CDC, historical data processing, metadata-driven automation frameworks and performance optimisation
• Teradata and Hadoop/Cloudera at scale: warehouses of 100 TB+ and tables of billions of rows
• Spark, Python, R, SQL, Hive, Impala, HBase, Pig and Hue; Apache Iceberg and Trino
• Streaming and integration: Kafka, Spark Streaming, Informatica (including IDL) and Talend
• Databases and data federation: advanced SQL, NoSQL, Denodo and Snowflake
• Cloud and DevOps: Kubernetes, Airflow, GitOps and CI/CD tools

Delivery and communication

• Running design authority forums and reviewing engineers' designs and code
• Writing design specifications that pass architecture, audit and regulatory review

Good-to-have Skills

• Databricks, Snowflake and Lakehouse platforms; data services on Azure, Google Cloud, Huawei Cloud or Alibaba Cloud
• BI and analytics platforms: Qlik Sense, Microsoft Power BI and Azure analytics services

Certifications (preferred)

TOGAF; Teradata Vantage; Cloudera; DAMA CDMP; Databricks or cloud architect