BlastPoint

SDET

• Design, build, and maintain scalable automated testing frameworks for platform, API, integration, functional, regression, and end-to-end testing.
• Own the regression testing strategy for critical customer-facing workflows.
• Establish practical load, performance, and reliability testing practices for key platform areas.
• Integrate automated tests into CI/CD pipelines and help define release quality gates.
• Partner with DevOps on QA environments, automated deployments, test data, and release validation.
• Use AI tools as a co-engineer to accelerate automation development, test design, defect analysis, documentation, and QA process improvements.
• Work with engineers to make features more testable from the start.
• Evaluate and implement testing tools for E2E, API, smoke, regression, performance, and integration testing.
• Improve bug triage, defect communication, root-cause visibility, and release-readiness reporting.
• Reduce reliance on manual QA through maintainable automation while preserving targeted exploratory testing.
• Mentor engineers and future QA contributors on test design, automation standards, and quality best practices.
• Bring structure, ownership, and practical QA discipline to a fast-moving startup engineering environment.
• Help mature BlastPoint’s QA culture as the engineering organization scales.

Senior Automation QA Engineer / SDET

Database Administrator

• Own database architecture, performance, reliability, security, and scalability for core platform systems.
• Use AI tools responsibly to accelerate database analysis, documentation, query tuning, troubleshooting, and workflow improvement.
• Design database approaches for both single-tenant and multi-tenant SaaS environments, including migration strategies between tenancy models.
• Improve tenant isolation, customer-specific data separation, scalability, and compliance-ready data architecture.
• Review and improve schemas, indexes, queries, migrations, and data access patterns.
• Optimize SQL performance, indexing strategies, execution plans, and database bottlenecks.
• Partner with Engineering and Data Engineering on schema design, data modeling, migrations, pipelines, and performance-sensitive application changes.
• Help define database strategies across OLTP systems, OLAP workloads, reporting layers, and data pipelines.
• Strengthen database security practices, including encryption at rest, field-level encryption, column-level encryption, key management, access controls, and auditability.
• Establish practical standards for database migrations, rollback planning, production readiness, monitoring, backups, and disaster recovery.
• Support load testing, capacity planning, and performance benchmarking for critical workflows.
• Collaborate with DevOps on AWS-hosted database infrastructure, environment strategy, access controls, and cost optimization.

Database Architect, DBA

Account Executive

• Identify, open, and close 6- and 7-figure enterprise deals
• Lead with tailored Value Hypotheses to engage C-level stakeholders
• Build ROI narratives and champion investment cases
• Collaborate across product, DS, and marketing on GTM refinement
• Create your own pitch decks, outreach, and simple ROI tools
• Shape how we sell — you won’t just execute playbooks, you’ll help write them
• Lead customer interactions and represent BlastPoint at industry trade shows and events
• Maintain HubSpot CRM and generate sales reports

Data Engineer

• Design, build, and maintain scalable data pipelines for ingestion, transformation, validation, and delivery
• Write clean, efficient Python code using Pandas and PySpark for data processing
• Optimize data workflows for performance, reliability, and cost
• Automate data onboarding workflows to increase speed and consistency
• Integrate client data with public and private data sources
• Identify and resolve data quality issues across the pipeline lifecycle
• Utilize AWS resources to manage data infrastructure
• Support and improve pipeline orchestration and job execution
• Contribute to system reliability, monitoring, and security best practices
• Partner with engineering, data science, and product teams to deliver data solutions
• Own projects from concept through production
• Communicate clearly on progress, tradeoffs, and outcomes