Data Product Architect

Qode•Pennsylvania, PA

2d•Hybrid

About The Position

We are seeking a senior Data Product Architect to define and govern the end-to-end architecture of enterprise data products within a centralized data product organization. This role is accountable for designing scalable, reusable, and compliant data architectures that translate core banking domains into high-quality data products. The position is primarily architectural, with selective hands-on involvement to establish reference patterns and guide delivery teams. You will partner closely with Data Product Managers, Platform teams, and Engineering leads to ensure alignment with enterprise standards, regulatory requirements, and long-term modernization goals.

Requirements

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).
Proficiency in Data Platforms: Hadoop, modern lakehouse architectures.
Experience with Streaming & Processing: Spark, Spark Streaming, Kafka.
Programming skills: Java, Spring Boot (design/review), Python.
Knowledge of Modeling & Analytics: Dimensional, canonical, domain-driven modeling; semantic layers.
Familiarity with Observability: Data observability and operational monitoring (ELK preferred).
Understanding of Governance & Security: Data governance, lineage, quality, and compliance.

Nice To Haves

Preferred Qualifications include banking or financial services experience (deposits, loans, transactions), familiarity with data mesh or domain-oriented operating models, experience supporting BI modernization initiatives, and exposure to Azure, AWS, or GCP in regulated enterprise environments.

Responsibilities

Define end-to-end architecture for data products 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-product design principles to ensure consistency and reusability.
Establish and govern data contracts and domain interfaces.
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.
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.
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.
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.
Act as the architectural authority for data products within the organization.
Review and approve solution designs and reference implementations.
Bridge enterprise architecture standards with delivery execution across teams.