Principal Database Engineer- Architecture/Engineering

Who we are Solera is a global leader in data and software services that strives to transform every touchpoint of the vehicle lifecycle into a connected digital experience. In addition, we provide products and services to protect life’s other most important assets: our homes and digital identities. Today, Solera processes over 300 million digital transactions annually for approximately 235,000 partners and customers in more than 90 countries. Our 6,500 team members foster an uncommon, innovative culture and are dedicated to successfully bringing the future to bear today through cognitive answers, insights, algorithms and automation. For more information, please visit . The Role Database Architect to design, implement, and maintain high-performance, scalable database solutions across multiple platforms, including on-premises, cloud, and hybrid environments. The ideal candidate will have a strong background in database architecture, performance tuning, and data modeling, with expertise in multiple database platforms, including relational databases (MSSQL, Oracle, MySQL, Postgres), NoSQL databases (MongoDB, Cosmos DB), and cloud-based data warehouses (Google Snowflake, AWS Redshift, Azure Synapse Analytics). Responsibilities: Database Architecture and Design: Design, implement, and maintain database architectures for OLTP and analytics workloads Develop data models, database designs, and data flow diagrams Collaborate with application teams to ensure database designs meet business requirements Establish and enforce database design standards and best practices Performance Tuning and Optimization: Analyze and optimize database performance using various tools and techniques (e.g., query optimization, indexing strategies, database parameter configuration) Identify and resolve performance bottlenecks and issues in RDBMS (MSSQL, Oracle,Postgres,MySQL) , NOSQL (MongoDB,CosmosDB) and DW solutions Develop and implement performance monitoring and alerting solutions Coding Standards and Best Practices: Develop and enforce coding standards for T-SQL, PL/SQL, MySQL, Postgres, and NoSQL databases Establish and enforce database design standards and best practices Collaborate with development teams to ensure coding standards are met Collaboration and Communication: Collaborate with cross-functional teams (e.g., Operations, application development, data science, IT operations) Communicate technical concepts and ideas to non-technical stakeholders Participate in industry events and conferences to stay current with industry trends and best practices Data Warehousing and Big Data: Design, implement, and maintain data warehouse solutions (e.g., Google Snowflake, AWS Redshift, Azure Synapse Analytics) Develop and implement data lake solutions (e.g., Hadoop, AWS S3, Azure Data Lake) Integrate with big data technologies (e.g., Spark, Hadoop) NoSQL and Emerging Technologies: Design for optimization, architect partition scheme for scalability, implement, and maintain NoSQL database solutions (e.g., MongoDB, Cosmos DB, Cassandra) Evaluate and implement emerging technologies (e.g., graph databases, time-series databases) Architect Cloud and Hybrid Database Solutions: Design, implement cloud-based database solutions (e.g., AWS RDS, Azure SQL Database, Google Cloud SQL) Leverage cloud-native features and services (e.g., AWS DMS, Azure Data Factory) Design and implement hybrid database solutions (e.g., on-premises to cloud, cloud to cloud) Requirements: 8+ years of experience in database architecture and design Strong performance tuning and optimization skills Proficiency in multiple database platforms (relational, NoSQL, cloud-based) Experience with data warehousing, big data, and emerging technologies Strong communication and collaboration skills Relevant certifications (e.g., Microsoft Certified: Azure Database Administrator, Oracle Certified Professional) Experience with Agile methodologies and DevOps practices Bachelor's degree in Computer Science or related field Nice to Have: Experience with ML models, AI, and LLM models Experience with cloud-native services (e.g., AWS Lambda, Azure Functions) Experience with monitoring tools (e.g., Datadog)