Data Architect/Lead Data Engineer

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.