Join our global Data Platform Engineering team, responsible for the database infrastructure that underpins BCG's data products, analytics, and AI capabilities. This senior, hands-on role focuses on designing highly scalable and reliable cloud-native database platforms, primarily on AWS, while driving automation and establishing firm-wide platform standards. We seek an experienced engineer who can independently identify needs, make critical technical decisions, and deliver solutions. A strong cloud database background with a drive for innovation in AI-enabling infrastructure is essential.

Design and manage scalable, resilient, and cost-efficient cloud-native database platforms, with a strong emphasis on AWS. Develop automated, self-service capabilities using Infrastructure as Code (Terraform), CI/CD, and Git workflows. Establish platform patterns, standards, and guardrails across a multi-cloud environment. Lead technical initiatives, translating business and engineering requirements into robust platform designs. Implement SRE principles, ensuring observability, performance tuning, and effective incident response. Champion secure-by-design practices for identity, access management, and data protection. Drive cloud cost transparency and optimization through FinOps disciplines. Collaborate with architecture, application, and data teams to deliver practical platform solutions. Provide technical guidance and mentorship to engineering colleagues. Evaluate emerging database technologies and lead proof-of-concept initiatives to support evolving AI and data needs.

A Bachelor's or Master's degree in Computer Science, Engineering, or a related field is required, alongside 8-10 years of experience in database, platform, or infrastructure engineering. Essential hands-on experience includes PostgreSQL and AWS managed database services (e.g., DynamoDB, OpenSearch) in production. Proficiency with Terraform and CI/CD pipelines for infrastructure automation is a must. A solid understanding of database performance at scale, including query optimization, indexing, and data distribution, is critical. Candidates must be self-directed, owning problems from design through delivery, and possess a genuine interest in the evolution of database platforms, particularly in relation to AI and analytics.