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Databricks Data Architect (Wealth Management Data Platform)

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SeniorZdalnie·WarszawaFull-time·B2B·Umowa o pracę

#463700·Dodano 12 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Databricks LakehouseSparkDelta LakeUnity CatalogWorkflow orchestrationdata vault 2.0integration architectureGovernance and securityWealth ManagementDatabricks Lakeflow

Podsumowanie oferty

Own the target-state architecture for an enterprise data platform in the Wealth Management domain. Define integration design and Data Vault architecture for a platform built on Databricks.

Wymagania

Strong experience designing Databricks Lakehouse architectures, including Spark, SQL, Delta Lake, Unity Catalog, and workflow orchestration concepts.
Proven experience architecting enterprise data platforms, preferably in financial services or Wealth Management environments.
Strong practical understanding of Data Vault 2.0 architecture.
Experience defining integration architecture for enterprise data landscapes with multiple source systems and consumption channels.
Experience designing governance and security models (Unity Catalog, RBAC/ABAC, row/column-level security, PII protection, and compliance).

Nice to have:

Experience in Wealth Management, Private Banking, Asset Management, Investment Management, Capital Markets, or broader financial services.
Experience with Databricks Lakeflow Connect, Lakeflow Spark Declarative Pipelines, and Lakeflow Jobs.
Experience designing platforms that support regulatory, audit, compliance, risk, and financial reporting requirements.
Experience with MDM concepts.
Experience with cloud infrastructure on AWS, Azure, or GCP.
Experience with AI/RAG, semantic search, Vector Search, embeddings, metadata filtering, source-grounded generation, or LLM-based data enrichment is a plus, but not a core requirement.
dbt experience.

Obowiązki

Own the target-state architecture for a Databricks-based data platform.
Define platform architecture, integration patterns, data flows, architectural principles, and delivery guardrails for the engineering teams.
Design scalable data ingestion, transformation, orchestration, and publication patterns using Databricks, Spark, SQL, Delta Lake, Unity Catalog, and Lakeflow where appropriate.
Lead the Data Vault architecture, including raw vault, business vault, hubs, links, satellites, historization patterns, PIT tables, bridge tables, and downstream consumption layers.
Define canonical data models for core Wealth Management entities such as clients, households, advisors, accounts, portfolios, holdings, transactions, products, instruments, mandates, risk profiles, fees, suitability, and regulatory classifications.
Design integration patterns across heterogeneous source systems, including CRM, portfolio management platforms, trading systems, custodians, market data providers, risk systems, reporting platforms, and compliance tools.

Benefity

Career development system with clear skill qualifications.
Flexible working hours aligned to your schedule.

Elastyczne godziny

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