Senior Data Architect

Hybrid in Columbus, OH, US • Posted 2 days ago • Updated 2 days ago
Contract Independent
Contract W2
12 Months
No Travel Required
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • API
  • Data Processing
  • Data Lake
  • Data Marts
  • Data Migration
  • Data Architecture
  • Data Engineering
  • Data Governance
  • Computer Science
  • Dashboard
  • Data Analysis
  • Collaboration
  • Communication
  • Computer Engineering
  • Business Intelligence
  • Business Process
  • Cloud Computing
  • Data Warehouse
  • Database Administration
  • Dimensional Modeling
  • Data Stewardship
  • Data Validation
  • Database
  • Data Modeling
  • Data Quality
  • Data Security
  • Data Structure
  • Agile
  • Analytical Skill
  • Analytics
  • Apache Parquet
  • Query Optimization
  • Regulatory Compliance
  • SQL
  • Orchestration
  • Performance Tuning
  • Python
  • Reporting
  • Microsoft Exchange
  • Migration
  • Modeling
  • Optimization
  • Management
  • Mentorship
  • Meta-data Management
  • IT Architecture
  • Information Technology
  • Interfaces
  • Technical Writing
  • Training
  • Version Control
  • Work Ethic
  • Semantics
  • Snow Flake Schema
  • Streaming
  • Testing
  • Documentation
  • ELT
  • ER/Studio
  • File Formats
  • JSON

Summary

Remote Position - candidates in Ohio only

Interviews will be remote

Job Title: DBA 4 (Senior Data Platform Architect & Governance Specialist)

Location Franklin County

Remote/ Onsite/

Hybrid Remote

Travel Required Yes –Meetings as needed

Preferred Education: Bachelor’s Degree in Data Analytics, Computer Science, Information Technology, Computer Engineering, or a closely related field.

Job Description: Key Responsibilities: 1. ELT Pipeline Engineering & Automation. a. Pipeline Orchestration: Designs and maintains programmatic, automated ELT pipelines (i.e. SQL, Python, or modern cloud data tools) to process data incrementally through the Medallion stages. b. Performance Tuning: Conducts query and cluster tuning for modern cloud data platforms, ensuring highly optimized compute usage during heavy data transformations and processing. c. Data Migration Execution: Writes robust code to safely migrate legacy databases and files into automated Lakehouse ingestion pipelines. 2. Advanced Data Modeling & Cloud Data Architecture. a. Lakehouse Strategy: Works with IT Architecture staff to design and implement a scalable, secure Medallion Data Architecture across cloud environments. b. Layer Optimization: Establishes standards, schemas, and file formats (i.e. Iceberg, Parquet) for ingestion and data lake processing. c. Analytical Modeling: Designs highly efficient physical and logical data structures within the Gold layer, including modern dimensions, facts, and business entity schemas. d. Schema Evolution: Builds resilient data models capable of handling semi-structured data (JSON, API payloads) alongside structured data, maintaining robust version control of data contracts. e. Semantic Layer Design: Transforms complex business reporting requirements into user-friendly semantic layers that support self-service business intelligence. 3. Develop and document standards/best practices. a. Creates documentation of pipelines, architecture, modeling, and migration efforts. 4. Data migrations, business process monitoring. a. Designs standards for the exchange of data between systems, including data security models 5. Reporting business intelligence. a. Understands business intelligence data needs. b. Defines the data warehouse/business intelligence design.

c. Implements data warehouses and data marts. d. Implements business intelligence tools and user interfaces. e. Implements enterprise reporting. f. Implements management dashboards and scorecards. g. Implements analytic applications. h. Replicates and transforms data for business intelligence. 6. Modern Data Governance, Metadata Management & Cataloging a. Metadata Integration: Manages and curates the Alation Data Catalog, ensuring all tables, schemas, and views across the Bronze, Silver, and Gold layers are thoroughly indexed, classified, and tagged. b. Lakehouse Data Lineage: Maps and monitors complex, end-to-end data lineage from source applications down to Gold-layer reporting assets within Alation. c. Data Quality Frameworks: Designs programmatic data validation and testing protocols at the boundary between the Bronze and Silver layers to enforce strict enterprise data stewardship. 7. Mentoring. a. Plans and conducts formal mentorship activities for peers and/or lower-level staff via verbal instruction or technical documentation.

Mandatory skills •5+ years of hands-on experience designing and implementing enterprise data warehouse, data lake, or Lakehouse solutions • Expert-level SQL skills, including query optimization, performance tuning, and development of complex analytical datasets • Experience developing automated ELT pipelines using Python, SQL, and modern cloud data platform technologies • 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 and associated data processing standards • Advanced experience with dimensional data modeling, including fact tables, dimensions, star schemas, and semantic layer design • Experience integrating structured and semi-structured data sources, including APIs, JSON, and file-based ingestion frameworks • 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 define technical standards, best practices, and architecture documentation for enterprise data platforms • Ability to work independently and lead complex, cross-functional data architecture and engineering initiatives • Excellent communication skills and ability to collaborate with technical teams, business stakeholders, and executive leadership

Certifications or Desired skills if any • Experience with Snowflake cloud-native architecture, including Snowflake Warehouses, Snowpark, Streams, Tasks, and secure data sharing • Familiarity with data modeling (i.e. ER Studio) and modern modeling methodologies • Experience working in Agile, iterative, or rapidly evolving solution environments • Experience with enterprise data cataloging, metadata management, and data lineage tools (e.g., Alation)

Nice To Have Skills • Strong work ethic/Time & attendance punctuality • Experience with dbt

Qualifying questions if

any · Candidates in OH – required

Skill
Required / Desired
Amount
of Experience

 

5+ years of hands-on experience designing and implementing enterprise data warehouse, data lake, or Lakehouse solutions
Required
 
 
Expert-level SQL skills, including query optimization, performance tuning, and development of complex analytical datasets
Required
 
 
Experience developing automated ELT pipelines using Python, SQL, and modern cloud data platform technologies
Required
 
 
Hands-on experience implementing and supporting Snowflake-based data engineering, data warehousing, and analytics solutions
Required
 
 
Experience designing and managing Medallion Architecture (Bronze, Silver, Gold) data platforms and associated data processing standards
Required
 
 
Advanced experience with dimensional data modeling, including fact tables, dimensions, star schemas, and semantic layer design
Required
 
 
Experience integrating structured and semi-structured data sources, including APIs, JSON, and file-based ingestion frameworks
Required
 
 
Hands-on experience administering enterprise data catalog and governance platforms such as Alation
Required
 
 
Experience implementing data governance, metadata management, data lineage, and data quality frameworks
Required
 
 
Experience executing data migration and modernization initiatives
Required
 
 
Ability to define technical standards, best practices, and architecture documentation for enterprise data platforms
Highly desired
 
 
Ability to work independently and lead complex, cross-functional data architecture and engineering initiative
Highly desired
 
 
Experience with Snowflake cloud-native architecture, including Snowflake Warehouses, Snowpark, Streams, Tasks, and secure data sharing
Highly desired
 
 
Familiarity with data modeling (i.e. ER Studio) and modern modeling methodologies
Highly desired
 
 
Experience with enterprise data cataloging, metadata management, and data lineage tools (e.g., Alation)
Nice to have
 
 
Experience with dbt
Nice to have
 
 
Bachelor’s Degree in Data Analytics, Computer Science, Information Technology, Computer Engineering, or a closely related field
Highly desired
 
Fingerprint background checks are a compliance requirement. Does your candidate agree and understand?
 
Where is your candidate currently located? City, State
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91103975A
  • Position Id: 9137048
  • Posted 2 days ago
Contact the job poster
VP

Viswanath Pala

Recruiter @ Atash Enterprises, LLC

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