Data Architect
Listed on 2026-06-22
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IT/Tech
Data Warehousing, Data Engineering, Database Administrator
Is it Permanent/
Contract:
Open for both
Is it Onsite/Remote/Hybrid: for London (4 days WFO, 1-day WFH mandatory)
Experience15+ years
About the RoleWe are seeking a senior Data Architect to join the engineering organisation as part of Project Compass. This programme is delivering next-generation capabilities across Accounts (Real-Time Ledger), Payments Engine, and Foreign Exchange – all of which generate, consume, and depend on high-quality, well-governed data at scale.
The Data Architect will own the end-to-end data architecture across spanning Snowflake as the enterprise data warehouse and a landscape of in-house application databases (relational, time-series, document, and in-memory stores) that serve real-time operational workloads. You will define how data flows from source systems into the warehouse, how application databases are modelled and managed, and how data products are exposed to downstream consumers within and beyond.
This is a hands‑on, delivery‑focused role. You will work closely with Integration Architects, platform engineers, and domain product teams to translate business data requirements into durable, governed, and scalable data solutions.
Key Responsibilities Data Architecture & Strategy- Define and own the data architecture target state, covering the Snowflake enterprise data warehouse, application databases, and the data flows that connect them
- Establish a unified data modelling standard across relational (PostgreSQL, Oracle), in‑memory (Redis), time‑series (Timescale DB / InfluxDB), and document (MongoDB) stores used by applications
- Design the data ingestion and movement architecture – real‑time CDC pipelines, batch ETL/ELT patterns, and event‑driven feeds from the NATS messaging layer into Snowflake
- Define data domain boundaries, ownership, and lineage standards aligned with Project Compass product domains (RTL, Payments, FX)
- Produce and maintain authoritative data architecture artefacts: entity‑relationship models, data flow diagrams, data dictionaries, and Architecture Decision Records (ADRs)
- Lead the design and evolution of the Snowflake data warehouse, including schema design (Raw / Conformed / Consumption layers), virtual warehouse sizing, and cost governance
- Define standards for data loading (Snowpipe, Streams & Tasks, external stages), transformation (dbt patterns), and data sharing across business units
- Establish Snowflake data access controls, row‑level security, dynamic data masking, and PII governance in line with regulatory requirements (GDPR, BCBS 239)
- Champion Snowflake best practices for performance tuning, clustering keys, materialised views, and query optimisation
- Evaluate Snowflake‑native capabilities (Snowpark, Cortex AI, Dynamic Tables) and recommend adoption where they accelerate data product delivery
- Govern the application database landscape across – reviewing schema designs, indexing strategies, and data lifecycle management across all in‑house databases
- Define patterns for operational data stores (ODS) that bridge real‑time application databases and the analytical warehouse layer
- Ensure consistency between transactional data models and their warehouse representations, minimising transformation complexity and maximising fidelity
- Set standards for database change management, migration tooling (Liquibase / Flyway), and schema versioning across the application estate
- Identify and remediate data quality issues at source, defining data contracts between application teams and downstream consumers
- Define and implement data governance frameworks covering data ownership, stewardship, classification (PII, sensitive, public), and retention policies
- Establish data lineage and cataloguing standards, working with tooling such as Apache Atlas, Collibra, or Snowflake Horizon Catalog
- Design and enforce data quality rules and SLAs at ingestion, transformation, and consumption layers
- Collaborate with the Risk and Compliance function to ensure data architecture meets BCBS 239 Risk Data Aggregation and Reporting requirements
- Champion Master Data Management (MDM) principles for shared reference data (counter party, instrument, currency)…
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