Job Description A customer within the automotive industry is looking for a Sr Data Architect to join their team in Marysville, OH. This person will help lead the design, development, and implementation of our enterprise data architecture. This role is instrumental in defining how data will be stored, consumed, integrated, and managed across the organization. The ideal candidate will bring a strategic mindset, strong technical expertise, and deep understanding of modern data platforms, governance, and architecture best practices. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements -10+ years of relevant experience in data modeling/architecture specifically building conceptual, logical, and physical data models -Expert level experience building data models in data modeling tools -Expert level communication working with stakeholders around 80-100% of the time Experience working on prem and in AWS Strong experience with relational and non-relational databases (e.g., SQL Server, PostgreSQL, MongoDB, Cassandra). Deep knowledge of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) and ETL/ELT pipelines. Expertise in data modeling, data lakes, data catalogs, and metadata management. Familiarity with streaming technologies (e.g., Kafka, Kinesis) and real-time data processing.