DATA Platfrom Architect

Job Title: Data Platform Architect

Location: Pittsburgh, PA / Dallas , TX / Cleveland, OH

Duration: Full time

Role Overview

We are seeking a

Data Platform Architect

to lead the

technical and functional architecture

of multiple enterprise data products within a centralized data product organization. This is a

senior, hands-on architectural role

responsible for shaping how data is ingested, modeled, governed, and consumed across banking domains.

The role requires strong depth across

data platforms, streaming, analytics, and governance

, along with the ability to translate

core banking processes

into scalable and reusable data products. You will work across multiple teams, guiding architecture while ensuring alignment with enterprise standards and regulatory requirements.

Key Responsibilities

Data Product \& Domain Architecture

• Define

end-to-end architecture

for multiple data products, from source systems to analytics and downstream consumption.

• Design and govern

logical, physical, and semantic data models

, including facts, dimensions, metrics, and hierarchies.

• Apply

domain-driven and data product–oriented design principles

to ensure reusability and consistency.

• Establish clear data contracts and interfaces between domains and platforms.

Platform \& Technical Architecture

• Architect solutions across

Hadoop-based platforms, modern data lakehouse architectures, and streaming systems

.

• Define patterns for

batch, near real-time, and event-driven processing

using Spark, Spark Streaming, and Kafka.

• Guide integration across

on-prem and cloud environments

, including hybrid architectures.

• Ensure architectural alignment with enterprise data platforms and BI ecosystems.

Application, Streaming \& Integration Design

• Design data services and ingestion frameworks using

Java and Spring Boot

.

• Leverage

Python

for data engineering, orchestration, and analytical workloads.

• Architect Kafka-based pipelines for ingestion, decoupling, and event-driven data products.
• Apply

graph database

patterns where relationship-centric modeling is required.

Analytics \& Semantic Layer Enablement

• Define enterprise-grade

semantic models

to support BI tools such as Power BI and Fabric.

• Ensure consistent business definitions across reports, dashboards, and analytics products.
• Enable one-to-many consumption models where a single data product supports multiple use cases.

Observability, Quality \& Operations

• Embed

data observability

into architecture, including monitoring, alerting, and performance metrics.

• Use

ELK stack (Elasticsearch, Logstash, Kibana)

for logging, diagnostics, and operational insights.

• Design for resiliency, scalability, and operational excellence in data platforms.

Governance, Security \& Compliance

• Integrate

data governance

, lineage, metadata, and data quality controls into all architectures.

• Ensure compliance with

security, privacy, and regulatory standards

typical of large financial institutions.

• Define ownership, stewardship, and lifecycle management for data products.

Collaboration \& Leadership

• Partner closely with

Data Product Managers, Tech Leads, Data Engineers, and Platform teams

.

• Review and approve solution designs, models, and implementations.
• Act as a bridge between

enterprise architecture standards and delivery execution

.

• Influence architectural decisions across multiple initiatives and data products.

Required Qualifications

• 8\+ years of experience in

data architecture, data engineering, or analytics architecture

roles.

• Strong hands-on expertise in

data modeling, lakehouse platforms, and streaming architectures

.

• Proven experience designing and governing

enterprise-scale data products

.

• Strong communication skills with both technical and business stakeholders.
• Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).

Skills \& Technical Expertise

• Data Platforms \& Processing
• Hadoop ecosystems, modern

data lakehouse architectures

• Apache Spark and

Spark Streaming

• Kafka for real-time and event-driven data pipelines
• Programming \& Integration
• Java

,

Spring Boot

for data services and ingestion frameworks

• Python

for data engineering and analytics

• Integration patterns across hybrid (on-prem \+ cloud) environments
• Modeling \& Analytics
• Dimensional, canonical, and domain-driven data modeling
• Semantic layer and BI architecture (Power BI, Fabric, Tableau)
• Graph database

modeling for relationship-intensive use cases

• Observability \& Operations
• Data observability, monitoring, and platform resilience
• ELK stack

for logging, metrics, and troubleshooting

• Governance \& Security
• Enterprise

data governance

, lineage, metadata, and quality

• Security, access control, and compliance in regulated environments

Preferred Qualifications

• Experience in

banking or financial services

, especially core banking domains (deposits, loans, transactions).

• Familiarity with

data mesh or domain-based data product operating models

.

• Experience supporting

BI modernization initiatives

• Exposure to cloud platforms (Azure, AWS, GCP) in regulated enterprise setups.

Best Regards,

Deepak Gulia

Sr. Talent Acquisition-USA