Enterprise Data Architect — Data Strategy Leader (Hybrid, Reading)

InSource, Inc; Reading (Berks County); Hybrid; USD 130,000 - 190,000; Full time

Job summary

InSource, Inc. in Reading, PA is seeking an Enterprise Data Architect to lead enterprise-wide data strategy across transactional, operational, and analytical platforms.

You will partner with business and technology leaders to drive data governance, MDM, and AI-ready architectures. The role defines standards, guides decisions across OLTP, ODS, Data Warehouse, Data Lake and Lakehouse, and mentors teams on governance.

Qualifications

• 12+ years of Data Architecture experience.
• Experience with Data Governance, MDM, and enterprise data modeling.
• Expertise in analytical platforms including Snowflake, Data Warehouse, and Lakehouse architectures.
• Strong understanding of transactional, operational, and analytical data ecosystems.
• Experience working with executive stakeholders and translating business needs into architecture solutions.
• AWS experience preferred; Azure or GCP experience also considered.

Responsibilities

• Define enterprise data architecture standards, roadmaps, and best practices.
• Lead architecture decisions across OLTP, ODS, Data Warehouse, Data Lake, and Lakehouse environments.
• Partner with business stakeholders to align data architecture with business objectives.
• Drive MDM, data governance, and data domain strategies.
• Establish AI-ready data foundations and analytical architectures.
• Evaluate modern data platforms, integration patterns, and cloud technologies.
• Mentor architects and engineering teams on architecture standards and governance.

Skills

Data Architecture

Data Governance

MDM

Snowflake

Data Warehouse

Lakehouse

AWS

Kafka

Spark

Flink

Tools

Snowflake

Kafka

Spark

Flink

AWS

Azure

GCP

Data Modeling Tools

Job description

InSource, Inc. in Reading, PA is seeking an Enterprise Data Architect to lead enterprise-wide data strategy across transactional, operational, and analytical platforms.

You will partner with business and technology leaders to drive data governance, MDM, and AI-ready architectures. The role defines standards, guides decisions across OLTP, ODS, Data Warehouse, Data Lake and Lakehouse, and mentors teams on governance.