Job Title: Data Architect
Location: Pittsburgh, PA / Dallas, TX / Cleveland, OH (Hybrid)
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.
Collaboration & Leadership
· 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.
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 Google Cloud Platform 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
Preferred Qualifications
· Banking or financial services experience (deposits, loans, transactions).
· Familiarity with data mesh or domain-oriented operating models.
· Experience supporting BI modernization initiatives.
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