Sr. Database Engineer to be a technical authority and lead designer of our high-performance data environments. You are a "builder" who views databases as code—equally skilled at deep SQL performance tuning as you are at building automated deployment pipelines for global-scale clusters.
You thrive on the challenge of high-stakes, large-scale data systems. As a key client-facing expert, you will guide our clients away from legacy "babysitting" models toward modern, self-healing, cloud-native database architectures on AWS.
What You’ll Do
· Architect Scalable Data Systems: Design and oversee the implementation of enterprise-scale relational (RDS, Aurora) and NoSQL (DynamoDB, DocumentDB) database architectures.
· Engineer Database Automation: Develop "Database-as-Code" using Terraform or CloudFormation to automate provisioning, scaling, and recovery processes across multi-region environments.
· Optimize for Performance: Act as the final authority on complex performance tuning, including query optimization, indexing strategies, and hardware-level bottleneck analysis.
· Modernize for AI: Design and implement specialized data storage solutions, such as vector databases (Amazon OpenSearch, pgvector), to support Generative AI and RAG-based applications.
· Set the Standards: Define and enforce best practices for data modeling, security (encryption at rest/transit), and high-availability/disaster recovery (RPO/RTO) across the practice.
· Lead & Mentor: Act as a technical mentor for junior engineers, leading deep-dive design reviews and fostering a culture of operational excellence.
What You Bring (Requirements)
· Professional Experience: 8-12+ years in database administration or engineering, with at least 4+ years in a Senior Engineering role focusing on cloud environments.
· AWS Database Mastery: Expert-level knowledge of the AWS database ecosystem (Aurora, RDS, DynamoDB, Redshift).
· Coding & Scripting: Proven mastery of Python and Advanced SQL for automation and sophisticated data manipulation.
· Infrastructure as Code (IaC): Deep experience with Terraform or AWS CDK to manage database infrastructure.
· Data Modeling: Expert-level understanding of both relational and non-relational data modeling techniques.
· Client-Facing Excellence: Exceptional skills in leading technical workshops and translating ambiguous business needs into high-performance technical designs.
· Startup Mentality: A "builder" mindset with a focus on impact, ownership, and the agility to solve "unsolvable" technical challenges.
Bonus Points (Nice-to-Haves)
· Certifications: AWS Certified Database – Specialty or AWS Certified Solutions Architect – Professional.
· AI/ML Fluency: Experience with vector databases and preparing data pipelines for LLM integration.
· Consulting Background: Experience in a Professional Services or global consulting environment.
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