SMASH

Manager

• Lead ERP needs assessment and software selection engagements from discovery through executive recommendation.
• Define business, functional, and technical requirements in collaboration with client stakeholders.
• Develop vendor shortlists, manage RFP/RFI processes, and coordinate ERP evaluations and demos.
• Facilitate executive-level workshops and decision-making sessions with client leadership teams.
• Serve as engagement or program lead with full accountability for scope, timeline, quality, and outcomes.
• Advise clients in manufacturing and operations-driven environments on ERP strategy and fit.
• Translate accounting, costing, and operational requirements into ERP selection criteria.
• Provide objective, vendor-agnostic guidance aligned to client business goals.
• Partner with internal teams to deliver high-quality advisory outputs and recommendations.
• Support transition planning from selection into implementation readiness, when applicable.

Senior ERP Manager

Customer Support

• Respond to inbound customer inquiries via phone and email, aiming for one-contact resolution.
• Analyze customer needs and provide clear, accurate solutions or information.
• Process customer payments using approved inbound and outbound collection methods.
• Communicate maintenance updates and service-related information via calls, email, or text.
• Serve as backup support for limited overflow sales, reservations, or rental requests.
• Document interactions and outcomes accurately in customer relationship management systems.
• Collaborate with internal departments to resolve issues efficiently while on the call.
• Demonstrate empathy, de-escalation, and professionalism in all customer interactions.
• Manage multiple tasks and systems simultaneously to resolve customer issues.
• Adhere to company guidelines, schedules, and service quality standards.

Customer Service Rep

Data Engineer

• Lead the design and implementation of enterprise-scale DataOps platforms and automation frameworks.
• Architect and evolve GCP-native data platforms supporting high-throughput batch and real-time workloads.
• Design and implement microservices-based data architectures using containerization technologies.
• Build and maintain CI/CD pipelines for data workflows, including automated testing and deployment.
• Develop Infrastructure as Code (IaC) solutions to standardize and automate platform provisioning.
• Implement robust data orchestration, monitoring, and observability capabilities.
• Establish and enforce data quality frameworks to ensure reliability and trust in data products.
• Support real-time data platforms operating at extreme scale.
• Partner with platform squads to deliver self-service data infrastructure products.
• Drive best practices for automation, resiliency, scalability, and operational excellence.
• Influence technical direction, mentor senior engineers, and lead through ambiguity.

Senior Data Operations Engineer – DataOps

Implementation Specialist

• Lead customer implementations following a defined four-week onboarding cycle.
• Map customer ERP, CLM, and AP workflows during discovery and requirements gathering.
• Configure system validation rules, approval thresholds, and confidence levels.
• Deploy connectors, configure SSO integrations, and ingest customer contract data.
• Process and validate historical invoice data, ensuring accuracy and performance benchmarks.
• Coordinate go-live activities, including production feed activation and post-launch monitoring.
• Conduct customer training sessions for AP and procurement teams.
• Configure contract-to-invoice mappings across categories, locations, and reimbursement rules.
• Coordinate with backend engineering teams to manage API, SFTP, EDI, and email integrations.
• Test data ingestion pipelines and validate contract extraction accuracy (90%+ target).
• Configure ERP write-back and webhook notifications for real-time alerts.
• Manage multiple concurrent customer implementations across pods and timelines.
• Troubleshoot configuration issues and escalate technical blockers effectively.

• You will design and operate scalable ETL and streaming pipelines that process contracts and invoices at high volume with strong data quality guarantees.
• This role focuses on building reliable data platforms that power analytics, ROI reporting, and compliance through robust governance, validation, and observability.
• Design and maintain ETL pipelines to ingest contracts and invoices from PDF, DOCX, CSV, Excel, and webhook sources.
• Build scalable workflows for historical data migrations (10K+ invoices per customer).
• Implement real-time streaming pipelines for event-driven integrations.
• Develop and manage an analytics data warehouse to support reporting, metrics, and trend analysis.
• Model customer-specific datasets for ROI, savings, and exception reporting.
• Implement data validation checks for completeness, accuracy, and consistency.
• Build data quality monitoring, alerting, and dead-letter queue handling.
• Implement PII/PHI detection, masking, and data retention policies (5-year audit trail).
• Track data lineage from source through transformation to consumption.
• Optimize SQL queries and data models for performance and scalability.
• Collaborate with product, engineering, and analytics teams to evolve data requirements.

• Design and implement a scalable, GCP-native data strategy aligned with machine learning and analytics initiatives.
• Build, operate, and evolve reusable data products that deliver compounding business value.
• Architect and govern squad-owned data storage strategies using BigQuery, AlloyDB, ODS, and transactional systems.
• Develop high-performance data transformations and analytical workflows using Python and SQL.
• Lead ingestion and streaming strategies using Pub/Sub, Datastream (CDC), and Cloud Dataflow (Apache Beam).
• Orchestrate data workflows using Cloud Composer (Airflow) and manage transformations with Dataform.
• Modernize legacy data assets and decouple procedural logic from operational databases into analytical platforms.
• Apply Dataplex capabilities to enforce data governance, quality, lineage, and discoverability.
• Collaborate closely with engineering, product, and data science teams in an iterative, squad-based environment.
• Drive technical decision-making, resolve ambiguity, and influence data architecture direction.
• Ensure data solutions are secure, scalable, observable, and aligned with best practices.

Senior Data Engineer

DevOps Engineer

• Ensure 99.5% uptime SLA across all production services and customer environments.
• Design and maintain multi-region deployments to support geographic redundancy.
• Implement automated failover mechanisms for databases, load balancers, and critical services.
• Build and manage disaster recovery strategies, including automated backups and point-in-time recovery.
• Lead incident detection, response, and postmortems, meeting defined SLAs for P0 issues.
• Develop real-time observability dashboards for uptime, latency, error rates, and system health.
• Monitor application and infrastructure performance metrics across customers.
• Implement alerting, on-call rotations, escalation policies, and PagerDuty integrations.
• Manage log aggregation and retention using SIEM platforms such as Splunk or Sumo Logic.
• Support SOC 2 Type II preparation through security controls, monitoring, and documentation.
• Implement vulnerability scanning, penetration testing coordination, and DLP controls.
• Optimize cloud infrastructure costs through right-sizing, auto-scaling, and storage lifecycle policies.
• Track and report infrastructure and API costs per customer, driving FinOps best practices.
• Build automated runbooks and self-healing workflows for common incidents.