Senior Data Architect & Analytics Lead

Roles and Responsibilities

• Serve as a technical resource for planning, developing, and maintaining data models and database structures to support global needs.
• Translate logical designs into physical databases and define data flows across systems.
• Plan, design, and document logical and physical enterprise relational data models.
• Facilitate and participate in design sessions with development, architecture, BI, data integration teams, and power users.
• Implement physical data models on platforms such as Snowflake.
• Gather and analyze data requirements by working with end users and stakeholders.
• Develop source-to-target mapping documents and document business transformation rules.
• Perform data quality analysis and profiling to ensure data integrity and accuracy.
• Support QA and end users during testing phases, including QA and User Acceptance Testing.
• Provide production support and ongoing maintenance for the enterprise data warehouse.
• Identify problematic data areas, research root causes, and recommend corrective actions.
• Support data governance initiatives through monitoring, queries, and process improvements.
• Clean, preprocess, and transform data from various sources, ensuring accuracy and quality.
• Identify KPIs, develop metrics, and create reports to measure business performance.
• Monitor and improve data quality, proposing enhancements or cleansing as needed.
• Stay current with industry trends and best practices in data analysis, modeling, and reporting.
• Communicate data modeling strategies and analytical insights to cross-functional teams and executives.

• Bachelor’s degree in Computer Science, Information Systems, or equivalent work experience.
• 7+ years of significant experience in data analysis, including 2–4 years building complex data models.
• 2+ years of experience in data profiling and quality assurance.
• 3–5 years of hands-on Snowflake experience, with ability to write complex SQL queries.
• Proficiency in SQL and Python for data manipulation and analysis.
• Experience with BI and data visualization tools such as SAP BO, Power BI, and Excel.
• Strong knowledge of data modeling, data warehousing, OLAP, and analytic database environments.
• Ability to create data flow diagrams, process flow diagrams, and complex relational data models.
• Knowledge of BI methodologies, Data Marts, and Data Warehousing concepts is a plus.
• Experience in professional services, accounting, or consultative technology roles is a plus.
• Strong analytical and problem-solving skills with the ability to interpret complex datasets.
• Proven ability to work with large datasets through cleaning, preprocessing, and transformation techniques.