Senior Database Engineer

Cvent is a leading meetings, events, and hospitality technology provider with more than 5,000+ employees and 24,000+ customers worldwide, including 60% of the Fortune 500. Founded in 1999, Cvent delivers a comprehensive event marketing and management platform for marketers and event professionals and offers software solutions to hotels, special event venues and destinations to help them grow their group/MICE and corporate travel business. Our technology brings millions of people together at events around the world. In short, we’re transforming the meetings and events industry through innovative technology that powers the human connection.

Cvent's strength lies in its people, fostering a culture where everyone is encouraged to think like entrepreneurs, taking risks and making decisions confidently. We value diverse perspectives and celebrate differences, working together with colleagues and clients to build strong connections.

Are you ready to shape the future of work at the intersection of human expertise and AI innovation? At Cvent, we’re committed to continuous learning and adaptation—AI isn’t just a tool for us, it’s part of our DNA. We’re looking for candidates who are eager to evolve alongside technology. If you love to experiment boldly, share your discoveries, and help define best practices for AI-augmented work, you’ll thrive here. Our team values professionals who thoughtfully integrate AI into their daily work, delivering exceptional results while relying on the human judgment and creativity that drive real innovation.

Throughout our interview process, you’ll have the chance to demonstrate how you use AI to learn, iterate, and amplify your impact. If you’re excited to be part of a team that’s leading the way in AI-powered collaboration, we’d love to meet you.

Cvent is seeking a Senior Database Engineer with deep Snowflake expertise to help design, manage, optimize, and secure our enterprise data platform across Cvent's portfolio of products. The ideal candidate will have strong hands-on experience with Snowflake as a primary platform, complemented by proficiency in cloud database technologies — with at least one being a relational database — and a strong desire to manage database technologies of all types. The candidate should also be familiar with Infrastructure as Code and other automation for managing databases at scale. As a Senior Database Engineer at Cvent, you will collaborate with development and data engineering teams to implement, optimize, and secure the data stores powering Cvent's products. You will build and use automation capable of managing enterprise-scale Snowflake environments while maintaining Cvent's standards and best practices. You will also help us continuously evaluate and improve those standards to ensure we provide the most resilient, scalable, performant, and secure database platforms possible

Design, develop, and manage Snowflake data platforms on AWS, including warehouse sizing, clustering, resource monitors, data sharing, and multi-cluster configurations

Architect and optimize Snowflake environments — virtual warehouses, storage layers, role-based access control (RBAC), and cost optimization strategies

Collaborate with cross-functional teams to understand data requirements and ensure databases and data platforms meet organizational needs

Implement and manage database security policies, including Snowflake RBAC, dynamic data masking, row-level security, access control, encryption, and backup and recovery procedures

Monitor database and platform performance and troubleshoot issues across Snowflake and supporting AWS database services

Optimize query performance through schema design, clustering keys, materialized views, query profiling, and indexing strategies

Ensure backup, disaster recovery, and time-travel procedures are in place, tested, and aligned with business RTO/RPO requirements

Develop and maintain database documentation, including data dictionaries, data models, Snowflake object inventories, and technical specifications

Automate database provisioning and management using Infrastructure as Code tools (Terraform, CloudFormation, or AWS CDK) and scripting (Python, PowerShell, or Bash)

Support AWS database services including Aurora, RDS (PostgreSQL/MySQL), Redshift, and DynamoDB as complementary platforms to Snowflake

Stay current with Snowflake releases, AWS database innovations, and AI/ML integrations (e.g., Snowpark, Snowflake Cortex, AWS Bedrock) and evaluate new capabilities for adoption

Bachelor's degree in Computer Science, Information Technology, or a related field

4–7 years of experience in database or data platform engineering, with at least 3 years of hands-on Snowflake administration

Deep expertise in Snowflake, including: – Virtual warehouse management and cost optimization – Snowflake security model (RBAC, data masking, network policies) – Data sharing, replication, and failover groups – Snowpipe, Tasks, Streams, and change data capture patterns – Performance tuning via query profiling, clustering keys, and materialized views

Experience managing highly available databases in AWS (Aurora, RDS, Redshift, or DynamoDB)

Expertise in Python or PowerShell scripting for automation and pipeline support

Deep understanding of database security principles — encryption, access control, auditing, and compliance frameworks (SOC 2, HIPAA, or GDPR)

Experience with Infrastructure as Code (Terraform, AWS CloudFormation, or AWS CDK) for consistent, repeatable deployments

Familiarity with ETL/ELT orchestration tools such as dbt, Apache Airflow, or AWS Glue in the context of Snowflake data pipelines

Strong understanding of SQL and data modeling principles, including normalization, dimensional modeling, and schema design

Snowflake certifications: SnowPro Core or SnowPro Advanced (Architect, Data Engineer, or Administrator)

AWS certifications: AWS Certified Solutions Architect, AWS Certified DevOps Engineer, or AWS Certified Database Specialty

Experience with Snowpark (Python or Java) for in-platform data transformation and ML feature engineering

Familiarity with AI/ML integrations — Snowflake Cortex, AWS SageMaker, or AWS Bedrock

Experience with document store technologies such as MongoDB or Couchbase

Exposure to Snowflake Data Marketplace and cross-account data sharing architectures

Experience with streaming data ingestion into Snowflake via Kafka, Kinesis, or Snowpipe Streaming

Hybrid: 2 days in office

Physical Demands