As a Database Engineer on the Professional Archive team, you'll operate as a subject-matter expert for the data infrastructure that powers our platform – driving the architecture, scaling, and reliability decisions that keep high-velocity, compliance-critical systems performant and secure. You'll work with SQL Server environments spanning multi-terabyte data volumes, tables with billions of rows, and sustained throughput exceeding 100,000 transactions per second.
You'll work independently through ambiguous and unfamiliar problems, set technical direction for real-time data pipelines and system performance, and act as a go-to resource for engineers across the wider organization. Your work will directly shape how Smarsh clients meet their compliance needs through scalable, dependable data and search capabilities.
You'll partner with leaders across Product Management, Engineering, and Site Reliability, weighing a range of inputs to resolve complex challenges and influence strategy beyond your immediate team. We're looking for someone who brings deep technical judgment, mentors others, and is motivated to make an impact through thoughtful, high-leverage engineering.
How will you contribute?
- Serve as a subject-matter expert for database architecture and performance, guiding engineers through complex or ambiguous technical problems where established principles don't fully apply
- Set the technical approach for scalable data solutions, partnering with stakeholders across Product, Engineering, and Site Reliability to shape direction rather than simply implement it
- Drive larger, cross-functional projects from design through delivery, proactively identifying and addressing upstream and downstream impacts before they become issues
- Informally mentor other engineers, modeling sound engineering discipline and raising the technical bar for the wider team
- Shape how the team adopts modern engineering practices, including Agile methodologies, CI/CD pipelines, and DevOps principles
- Review code and database changes with an eye for systemic risk and performance, while also leading efforts to pay down technical debt across systems
- Track emerging technologies and make the call on which are worth adopting, guiding the team's direction
- Interpret database health and performance data (Splunk, Datadog, Grafana) to proactively flag and address risk before it surfaces as an incident
What will you bring?
We're looking for a recognized subject-matter expert who operates independently, drives clarity through ambiguity, and raises the bar for those around them.
Preferred Qualifications
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If you don't meet every qualification listed below, we still encourage you to apply. We value diverse experiences and perspectives. Progression to this level reflects demonstrated ability to perform as a subject-matter expert, not years of experience alone.
- 7+ years of hands-on experience with Microsoft SQL Server in a production environment, with demonstrated impact as a subject-matter expert
- Deep expertise in schema and data model design, including normalization, partitioning, and indexing strategy for both OLTP workloads
- Advanced proficiency in performance tuning, including T-SQL and stored procedure optimization, execution plan analysis, and query tuning at scale
- Proven, hands-on experience managing and troubleshooting SQL Server databases at terabyte scale, including tables with billions of rows, and sustained throughput exceeding 100k transactions per second
- Demonstrated ability to diagnose and resolve production capacity and contention issues at this scale, including lock/latch contention, TempDB performance, and transaction management
- Experience designing for horizontal as well as vertical scalability, anticipating data growth before it becomes a production risk
- Familiarity with NoSQL technologies (e.g., MongoDB, Cassandra, DynamoDB) is a plus
- Experience with cloud database platforms (e.g., AWS RDS/Aurora, MongoDB Atlas) is a plus
What do we offer?
Skills
SQL Server — Database Architecture — Data Infrastructure — Real-time Data Pipelines — System Performance Optimization — Scaling — SQL — High-throughput Systems