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Data Architect - Banking

Job Description - Data Architect - Banking

Description

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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