Senior/Staff Database Engineer, Platform Engineering at HG Insights

<p></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><strong>About HG Insights</strong></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Headquartered in Santa Barbara, California, HG Insights is the global leader in technology intelligence. We help the world's most innovative companies accelerate their go-to-market efforts with precision through advanced data science methodologies and proprietary data assets. We offer a culture that blends innovation, collaboration, and growth, where each team member is empowered to make a measurable impact.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><strong>Role Overview</strong></p> <p>HG Insights runs data infrastructure across three organizations, two clouds, and sixteen database and caching technologies. As we scale, we're consolidating database ownership under Platform Engineering. This role leads that function.</p> <p>You will be the first database specialist on our DevOps team; embedded, not siloed. You'll own the full database portfolio: operational health, security posture, cost optimization, and the migration work required to modernize our data layer. As you build the practice, you'll cross-train DevOps engineers so the capability compounds beyond one person.</p> <p>This is a Senior/Staff individual contributor role. You will set direction on database strategy and own its execution. The team you're joining manages 140+ IaC repositories across AWS, GCP, and Kubernetes.</p> <p><strong>Job Overview&nbsp;</strong></p> <h2><span style="font-size: 12pt;">_{<strong>What You'll Own</strong>}</span></h2> <p><strong>Database ownership across the portfolio</strong></p> <ul> <li>Primary operator for PostgreSQL (RDS, Aurora, Cloud SQL, NeonDB), MySQL, Redshift, ClickHouse, Elasticsearch, OpenSearch, MongoDB Atlas, and Databricks</li> <li>Caching layer ownership: ElastiCache Redis, Dragonfly, Valkey</li> <li>Version management and patching across a multi-repo Terraform estate; coordinate EOL remediations across AWS and GCP</li> <li>Establish backup, recovery, and DR standards across all managed data layers</li> </ul> <p><strong>Migration and modernization</strong></p> <ul> <li>Lead Elasticsearch modernization; approved architecture, ready to execute</li> <li>Lead ClickHouse stabilization and standardization</li> <li>Phoenix data repatriation: move third-party-hosted data in-house as Phoenix migration progresses</li> <li>NeonDB consolidation evaluation</li> </ul> <p><strong>Performance and cost</strong></p> <ul> <li>Own database cost optimization across the portfolio: capacity planning, rightsizing, reserved instance and savings plan recommendations</li> <li>Query analysis, slow query identification, connection pool tuning</li> <li>Identify and execute on addressable savings in the database infrastructure spend</li> </ul> <p><strong>Platform integration</strong></p> <ul> <li>Terraform and Terraform Cloud for all database infrastructure; standardize configurations across a fragmented estate</li> <li>ArgoCD and Kubernetes (EKS, GKE) for database workloads running in-cluster (Elasticsearch, ClickHouse, Dragonfly)</li> <li>GitHub Actions CI for database migration testing and backup validation</li> <li>Build and own the database observability layer in Datadog: dashboards, monitors, slow query alerting, replication lag, connection saturation</li> </ul> <p><strong>Collaboration with application engineering</strong></p> <ul> <li>Partner with application engineering teams on database design, schema changes, query optimization, and technology selection; you are the subject matter authority they escalate to</li> <li>Establish and maintain standards for how application teams interact with the data layer: migration tooling, connection management, index design review, and capacity requests</li> <li>Own the feedback loop between application performance and database infrastructure; connect slow query data to engineering teams who can act on it</li> </ul> <p><strong>Cross-training and knowledge transfer</strong></p> <ul> <li>Structured cross-training with the DVO team so database operational capability isn't concentrated in one person</li> <li>Document operational runbooks, incident response procedures, and capacity planning models</li> </ul> <h5><span style="font-size: 12pt;"><strong>What We're Looking For</strong></span></h5> <ul> <li>5+ years of hands-on database administration or database engineering; not theoretical</li> <li>Deep PostgreSQL expertise: replication, vacuum tuning, connection pooling (PgBouncer/PgCat), index strategy, major version upgrades</li> <li>Elasticsearch operational experience at scale; index lifecycle management, shard sizing, snapshot/restore, Kubernetes-hosted clusters</li> <li>ClickHouse or columnar database experience is a strong plus</li> <li>AWS RDS, Aurora, Redshift, ElastiCache; day-to-day operations, not just provisioning</li> <li>Terraform and Terraform Cloud; you will be reading and writing IaC on day one</li> <li>Kubernetes (EKS or GKE); database workloads run in-cluster and you need to be comfortable there</li> <li>Python or Bash scripting; maintenance windows, backup validation, migration tooling</li> <li>Migration experience; schema migrations, cross-engine moves, zero-downtime cutover strategies</li> <li>Datadog or equivalent observability tooling</li> </ul> <p><strong>Nice to have</strong></p> <ul> <li>BigQuery, DynamoDB, or Databricks administration</li> <li>Redis/Valkey/Dragonfly at production scale</li> <li>MongoDB Atlas administration</li> <li>Cloud cost optimization (reserved capacity, savings plans)</li> </ul>