Databricks Data Architect: Remote Wealth Management Lakehouse

Itransition; Polska; Hybrid; PLN 240,000 - 360,000; Full time

Benefits offered by this job

Flexible working hours

Options to work remotely

Corporate medical insurance

English courses online

Internal conferences and workshops

Job summary

Itransition is seeking a Databricks Data Architect to lead the Wealth Management Data Platform design and delivery. The role focuses on platform architecture, data Vault patterns, governance, and scalable, auditable data flows across CRM, portfolio, trading, and reporting systems.

You will define target-state architecture, integration patterns, and canonical models for clients, accounts, portfolios, and regulatory data, guiding engineering teams in evolving the data platform.

Qualifications

• Strong experience designing Databricks Lakehouse architectures for enterprise data platforms.
• Proven track record in financial services or Wealth Management contexts.
• Deep understanding of Data Vault 2.0, data governance, and security models.

Responsibilities

• Own the target-state architecture for a Databricks-based data platform.
• Define platform architecture, data flows, integration patterns, and guardrails.
• Design scalable ingestion, transformation, and orchestration using Spark, SQL, Delta Lake.
• Lead Data Vault architecture including hubs, links, satellites, historization.
• Define canonical data models for Wealth Management entities and related data layers.

Skills

Databricks Lakehouse architecture

Spark

SQL

Delta Lake

Unity Catalog

workflow orchestration

Tools

Lakeflow Connect

Lakeflow Spark Declarative Pipelines

Lakeflow Jobs

dbt

AWS

Azure

GCP

Job description

Itransition is seeking a Databricks Data Architect to lead the Wealth Management Data Platform design and delivery. The role focuses on platform architecture, data Vault patterns, governance, and scalable, auditable data flows across CRM, portfolio, trading, and reporting systems.

You will define target-state architecture, integration patterns, and canonical models for clients, accounts, portfolios, and regulatory data, guiding engineering teams in evolving the data platform.