Senior Data Platform Architect

S R INTERNATIONAL INC

2d•Remote

About The Position

The State of Ohio is seeking a Senior Data Platform Architect & Governance Specialist (DBA 4) to design, develop, and maintain enterprise data warehouse, data lake, and Lakehouse solutions. The role leads automated ELT pipeline development, Snowflake-based data engineering, and scalable Medallion Architecture (Bronze, Silver, Gold) data platforms. The position focuses on advanced data modeling, data migration, enterprise data governance, metadata management, data lineage, and data quality using platforms such as Snowflake and Alation. The successful candidate collaborates with IT architecture teams, business stakeholders, and technical teams to establish enterprise data standards, optimize data platforms, and support modern business intelligence initiatives. The position is 100% remote for Ohio candidates, with travel as needed for meetings. The engagement duration is through 06/30/2027.

Requirements

At least 5 years of hands-on experience designing and implementing enterprise data warehouses, data lakes, or Lakehouse solutions.
Expert-level SQL skills, including query optimization, performance tuning, and complex analytical dataset development.
Experience developing automated ELT pipelines using Python, SQL, and modern cloud data platforms.
Hands-on experience implementing and supporting Snowflake-based data engineering, data warehousing, and analytics solutions.
Experience designing and managing Medallion Architecture (Bronze, Silver, Gold) data platforms.
Advanced experience with dimensional data modeling, including fact tables, dimensions, star schemas, and semantic layers.
Experience integrating structured and semi-structured data, including APIs, JSON, and file-based ingestion.
Hands-on experience administering enterprise data catalog and governance platforms such as Alation.
Experience implementing data governance, metadata management, data lineage, and data quality frameworks.
Experience executing data migration and modernization initiatives.
Ability to work independently and lead complex, cross-functional data architecture and engineering initiatives.
Excellent communication and collaboration skills.

Nice To Haves

Experience with Snowflake cloud-native architecture, including Snowflake Warehouses, Snowpark, Streams and Tasks, and Secure Data Sharing.
Familiarity with data modeling tools such as ER/Studio.
Experience with modern data modeling methodologies.
Experience defining enterprise data architecture standards and best practices.
Experience leading cross-functional data architecture and engineering initiatives.
Bachelor's degree in Data Analytics, Computer Science, Information Technology, Computer Engineering, or a related field.
Experience with dbt.
Experience with enterprise data cataloging, metadata management, and data lineage tools such as Alation.
Strong work ethic, punctuality, and time-management skills.

Responsibilities

Design, develop, and maintain automated ELT pipelines using SQL, Python, and modern cloud data technologies.
Implement incremental data processing across Medallion Architecture layers.
Optimize SQL queries, compute resources, and cluster performance.
Develop solutions to migrate legacy databases and files into automated Lakehouse pipelines.
Design and implement scalable, secure Medallion Data Architecture across cloud environments.
Establish standards for data ingestion, schemas, and file formats such as Iceberg and Parquet.
Design logical and physical data models, including fact tables, dimensions, and business entity schemas.
Build data models that support structured and semi-structured data, including JSON and API payloads.
Develop semantic layers for self-service business intelligence and reporting.
Manage and maintain the Alation Data Catalog.
Ensure tables, schemas, and views across Bronze, Silver, and Gold layers are indexed, classified, and tagged.
Establish and monitor end-to-end data lineage from source applications to reporting assets.
Implement data validation, testing, and data quality frameworks.
Support enterprise data stewardship and governance standards.
Design and implement data migration and modernization solutions.
Establish standards for secure data exchange between systems.
Design and implement data warehouses and data marts.
Develop enterprise reporting, management dashboards, scorecards, and analytical applications.
Replicate and transform data to support business intelligence requirements.
Define data warehouse and BI architecture standards.
Develop technical documentation covering pipelines, architecture, data modeling, and migration processes.
Establish enterprise technical standards and best practices.
Mentor peers and junior technical staff through formal instruction and documentation.
Collaborate with business stakeholders and technical teams on architecture and engineering initiatives.