What are the responsibilities and job description for the Data Architect position at Incedo Inc.?
Job Title: Data Architect
Location: Pittsburgh, PA(Hybrid)
About Incedo:
Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business and technology across Banking & Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences.
We are building Incedo 4.0 - an AI-native, execution-focused, founder-led organization designed for scale, speed, and long-term impact.
Incedo delivers ROI from AI @ Scale through the “Power of 3”:
• Deep domain expertise
• AI & Data capabilities
• Engineering & Operations excellence
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.
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 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
Preferred Qualifications
- Banking or financial services experience (deposits, loans, transactions).
- Familiarity with data mesh or domain-oriented operating models.
- Experience supporting BI modernization initiatives.
Best Regards,
Deepak Gulia
Sr. Talent Acquisition-USA