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# Senior Data Scientist / Data Architect - C2H

- **Company:** SmartIMS Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Engineering, Information Systems, Customer Data Management, Data as a Services, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Normalization, Data Warehousing, Information Lifecycle Management, Meta-Data Management, MySQL, Oracle Databases, Oracle (Applications), Performance Tuning, Standard Sql, Azure Machine Learning, Salesforce.Com, Enterprise Data Management, Cloud Platform System, Data Ingestion, Snowflake, Data Strategy, Data Lakes, Information Technology, Data Analytics, Transactional Database, Data Management, Physical Data Models, Data Pipelines, Databricks
- **Published:** October 20, 2026
- **Apply:** https://www.dice.com/job-detail/64e8f297-348f-455a-b016-aaac4313e086

## About the Role

Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Engineering, or related field.
Minimum 15+ years of experience in Data Architecture, Data Science, Data Engineering, or related disciplines.
Strong expertise designing and implementing enterprise Data Warehouses and Data Lake solutions.
Hands-on experience with:
Databricks
Snowflake
Oracle Database
MySQL
Salesforce Data Integration
Deep understanding of data modeling, data governance, data quality, ETL/ELT frameworks, and enterprise architecture principles.
Experience building scalable cloud-based data platforms.
Strong SQL, data transformation, and analytics skills.
Ability to translate complex business requirements into scalable technical solutions.
Excellent communication, presentation, and stakeholder management skills., Experience with AWS data services and cloud-native architectures.
Knowledge of AI/ML platforms and enterprise AI enablement strategies.
Experience with data cataloging, metadata management, and governance frameworks.
Certifications in Databricks, Snowflake, AWS, or enterprise data architecture.
Experience leading enterprise data modernization and digital transformation initiatives.

## Description

We are seeking a highly experienced Data Scientist / Data Architect to lead the strategic assessment, design, and optimization of our enterprise data ecosystem. The organization recently acquired a company specializing in Data Warehouse and Data Lake services and is expanding its data capabilities across multiple business units and client engagements.

This role will be responsible for evaluating the current data environment, defining a long-term data strategy, and leading the normalization, governance, and optimization of large-scale enterprise data assets. The ideal candidate will spend the initial 3-6 months assessing the existing architecture, identifying opportunities for improvement, developing a roadmap, and assisting with implementation., Analyze and assess the current enterprise data landscape, including Oracle, MySQL, Databricks, Snowflake, and Salesforce environments.
Develop a comprehensive data strategy focused on data normalization, quality, governance, scalability, and performance optimization.
Design and implement enterprise Data Warehouse and Data Lake architectures to support business intelligence, reporting, analytics, and AI initiatives.
Lead data modeling efforts, including conceptual, logical, and physical data models.
Develop frameworks and best practices for data ingestion, transformation, integration, master data management, and metadata management.
Optimize data pipelines and ETL/ELT processes within Databricks and Snowflake environments.
Define standards for data governance, security, compliance, and data lifecycle management.
Collaborate with business stakeholders, data engineers, application teams, and executive leadership to align data architecture with organizational goals.
Integrate and streamline data from Salesforce and other enterprise platforms, including potential AWS-based data sources.
Provide recommendations on future-state architecture, technology adoption, and AI readiness.
Support the organization's strategy to leverage Salesforce beyond a transactional database and prepare data foundations for AI and advanced analytics initiatives.
Lead implementation efforts and mentor internal teams on data architecture best practices.