150K MAX
Role Overview
We are seeking a Data Architect to define and govern the end-to-end architecture of enterprise data products and platforms. This role is accountable for designing scalable, reusable, and compliant data architectures that translate core banking domains into high-quality data products and solutions. The position is primarily architectural, with selective hands-on involvement to establish reference patterns and guide delivery teams.
You will partner closely with Data Managers, Platform teams, and Engineering leads to ensure alignment with enterprise standards, regulatory requirements, and long-term modernization goals.
Key Responsibilities
Data & Domain Architecture
Define end-to-end architecture for data solutions from source systems through analytics and downstream consumption.
Design and govern logical, physical, and semantic data models (facts, dimensions, metrics, hierarchies).
Apply domain-driven and data-solutions design principles to ensure consistency and reusability.
Establish and govern data contracts and domain interfaces.
Platform & Streaming Architecture
Define architectural patterns across Hadoop, lakehouse, and streaming platforms.
Guide batch, near-real-time, and event-driven designs using Spark and Kafka.
Ensure alignment across on-prem and cloud-based platforms in a hybrid enterprise environment.

Application & Integration Architecture
Review and guide ingestion and data service designs built on Java/Spring Boot and Python.
Architect Kafka-based pipelines for decoupled, event-driven data products.
Apply graph modeling patterns where relationship-centric use cases require it.

Analytics & Semantic Enablement
Define enterprise semantic models supporting BI and analytics tools (Power BI, Fabric, Tableau).
Ensure consistent business definitions and metrics across reporting and analytics.
Enable one-to-many consumption where a single data product supports multiple use cases.

Governance, Quality & Compliance
Embed data quality, lineage, metadata, and observability into architectural designs.
Partner with centralized governance, security, and risk teams to meet regulatory requirements.
Define data product ownership, stewardship, and lifecycle standards.

Required Qualifications
12+ years of experience in data architecture, data engineering, or analytics architecture.
Proven experience designing enterprise-scale data products and platforms.
Strong expertise in data modeling, lakehouse architectures, and streaming systems.
Excellent communication skills with technical and business stakeholders.
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).

Technical Skills
Data Platforms: Hadoop, modern Lakehouse architecture
Streaming & Processing: Spark, Spark Streaming, Kafka
Exposure to at least one of the public cloud out of Azure, AWS, or GCP in regulated enterprise environments.
Programming: Java, Spring Boot (design/review), Python
Modeling & Analytics: Dimensional, canonical, domain-driven modeling; semantic layers
Observability: Data observability and operational monitoring (ELK preferred)
Governance & Security: Data governance, lineage, quality, and compliance

Enterprise Data Architect

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