Data Architect - Banking
Unison Group Open · verified Oct 24, 2026 At a glance
Mid-level Data Architecture & Governance role at Unison Group. Singapore · contract.
Pay not stated Data Architect salary
dataroles summary, based on the employer's posting.
What you'll do
- Design data platforms and banking models for customer, account, payments and financial crime or regulatory data
- Build warehouse, lake and Lakehouse designs, including historical models and data products
- Develop ETL/ELT, change-data capture and historical processing, while tuning large Teradata and Hadoop environments
- Set up batch and API data services with lineage, observability and service-level monitoring
- Lead design reviews, check engineers’ work and write specifications for architecture, audit and regulatory approval
What you bring
- At least ten years working with data, including four or more years in banking and practical data engineering experience
- Experience designing platforms within tier-one or large regional banks, with banking models such as Teradata FSLDM or an equivalent
- Background building financial-crime or regulatory data marts to BCBS 239 requirements for lineage, reconciliation and audit
- Hands-on expertise with Teradata and Hadoop or Cloudera at large scale, plus ETL/ELT, CDC and performance tuning
Who this fits
This contractor role is for a mid-level data architect with substantial banking and hands-on engineering experience. You’ll work onsite in Singapore. The work includes design authority and review responsibilities alongside architecture and engineering delivery.
From the employer
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
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