United States onlyWe are a fast-growing startup powering digital guest engagement for thousands of restaurants in North America. Our platform is pillared on commerce, engagement and intelligence. Data is key to our efforts, especially around warehousing, analytics and agentic AI. We are looking for a highly skilled and motivated database engineer to join our fast-paced team. The ideal candidate will have deep expertise in coding, designing, managing, and optimizing relational and columnar databases while ensuring scalability, performance, and reliability across multiple platforms. You will play a key role in serving up data to the API and front-end teams. You have to be self-driven with a proven ability to maintain mission-critical data environments.
Requirements
Job Responsibilities include:
Design, implement/code, and optimize relational MySQL, MongoDB and EMR databases.
Build and manage data warehouses and columnar databases for analytics and reporting.
Write, tune, and review complex SQL queries, stored procedures, and performance optimizations.
Ensure database scalability, security, and high availability in production environments.
Implement backup, recovery, and disaster recovery strategies.
Collaborate with engineering and data science teams to support data-driven applications and pipelines.
Work closely with product teams and US-based clients, ensuring smooth communication across time zones.
Troubleshoot production database issues with a focus on root cause analysis and prevention.
Requirements:
Experience working on AWS-based infrastructure (RDS, Redshift, DynamoDB, etc.) for database hosting and management.
4+ years of experience as a Database Engineer or similar role.
Proven hands-on expertise with MySQL, EMR, MongoDB, and data warehouse solutions.
Strong background in AWS cloud database services (RDS, Redshift, Aurora, DynamoDB).
Deep proficiency in SQL optimization and query performance tuning.
Experience designing and maintaining scalable ETL processes and data pipelines.
Familiarity with database monitoring tools and performance profiling.
Strong understanding of ACID principles, indexing, partitioning, replication, and sharding.
Experience working in fast-paced startup environments.
Excellent communication skills and ability to work with international teams and clients.
Preferred Qualifications
Experience with big data technologies (Spark, Hadoop) is a plus.
Knowledge of DevOps practices (CI/CD, infrastructure as code, Kubernetes).
Exposure to data modeling for machine learning and analytics pipelines.
Highlights
A dynamic startup culture with ownership and autonomy.
Opportunity to work on high-impact projects
Competitive compensation and growth opportunities.
Must have authorization to work in the United States
