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# Senior Solution Architect - I&D

- **Company:** Capgemini
- **Location:** Franklin Lakes, NJ, United States
- **Experience:** Expert
- **Salary:** $170,102.0 - $265,762.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Data Architecture, Data Governance, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Distributed Computing Environment, Apache Hadoop, Machine Learning, NoSQL, Power BI, Standard Sql, Data Streaming, Tableau (Software), Cloud Platform System, Snowflake, Apache Spark, Data Lakes, Information Technology, AWS Glue, Star Schema, Apache Kafka, Data Pipelines, Databricks
- **Published:** August 6, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=9ed54c8ce6b401fd

## About the Role

* Cloud Proficiency: Deep, hands-on expertise in at least one major cloud platform (AWS, Microsoft Azure, or GCP).
 * Data Modeling: Advanced knowledge of SQL and NoSQL databases, with mastery of modeling patterns like Star Schema, Kappa, or Lambda.
 * Big Data Technologies: Proven experience with distributed computing frameworks, including Apache Spark, Hadoop, or Kafka.
 * Experience: 8-12+ years in IT, with a minimum of 5 years dedicated specifically to data architecture or engineering.
 * Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

## Description

stakeholder management
data architecture
Power BI
performance optimization
Microsoft Azure
SQL/NoSQL Databases
Tableau
ETL/ELT

As a Senior Data Architect, you will serve as a technical leader responsible for the end-to-end design and implementation of robust data systems. You will bridge the gap between complex business requirements and actionable technical insights, specializing in the entire data lifecycle-from ingestion and storage to advanced analytics and visualization.

Core Responsibilities:

 * Architectural Blueprinting: Design and oversee scalable, secure data platforms, including Data Lakes, Data Warehouses, and modern Lakehouse architectures.
 * Data Pipeline Strategy: Define and lead the strategy for ETL/ELT pipelines, ensuring seamless data integration across disparate sources and maintaining high-quality data flow.
 * Technology Selection: Evaluate and select optimal tech stacks (e.g., Snowflake, Databricks, AWS Glue) by balancing cost, performance, and project constraints.
 * Governance & Security: Establish comprehensive frameworks for data governance, privacy compliance (GDPR), and high-level security protocols, including encryption and access control.
 * Stakeholder Liaison: Act as a translator between business executives and technical teams, providing clear architectural guidance to engineers while presenting technical value to stakeholders.
 * Advanced Analytics Support: Build infrastructure specifically optimized for Machine Learning (ML), AI, and Business Intelligence (BI) tools such as Power BI or Tableau.


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