BorderlessMind

• Own and manage the full month-end close process across multiple operating entities • Ensure all journal entries, reconciliations, and period-end deliverables are completed accurately and on time • Drive continuous improvement initiatives to shorten close timelines and improve efficiency • Prepare and maintain monthly balance sheet reconciliations for all accounts • Investigate and resolve variances in a timely manner • Maintain clear supporting documentation and audit-ready records • Prepare and update weekly and monthly KPI dashboards • Provide management with timely visibility into financial and operational performance • Participate in ERP implementation and optimization projects • Assist with workflow testing, user acceptance testing (UAT), and process documentation • Identify opportunities to improve accounting processes, controls, and system utilization • Assist with onboarding and integrating newly acquired businesses • Support opening balance sheet setup and chart of accounts mapping • Transition acquired entities into standardized accounting processes and reporting structures

• Lead NetSuite discovery workshops and solution design sessions • Configure and customize NetSuite modules across Finance, Operations, Inventory, and Warehouse Management • Develop SuiteScript 2.x customizations, workflows, dashboards, and saved searches • Design and support integrations using REST, SOAP, SuiteTalk, and OAuth 2.0 • Build and optimize warehouse workflows including pick-pack-ship, replenishment, cycle counting, and scanner integrations • Support multi-subsidiary, multi-currency, and inventory management implementations • Create functional specifications, configuration workbooks, and client status reports • Provide ongoing system enhancements, troubleshooting, and managed services support • Collaborate with finance, operations, and leadership stakeholders to improve business processes

• Design, build, and stabilize Databricks-based data pipelines • Perform pipeline optimization and production hardening • Develop and support reporting and data visualization solutions • Implement best practices for performance, scalability, and cost optimization • Work on end-to-end data workflows (ingestion → transformation → reporting) • Identify and resolve performance bottlenecks and system inefficiencies • Bring structure and consistency to an evolving Databricks environment • Collaborate with cross-functional teams to improve platform reliability and ROI

• Design and implement data solutions using Microsoft Fabric and OneLake • Build and maintain Lakehouse and Warehouse structures using Delta Lake • Develop data ingestion and orchestration using Fabric Data Pipelines • Create transformation logic using Spark / PySpark / SQL • Enable analytics consumption through Power BI Direct Lake • Implement CI/CD, data governance, and security best practices • Troubleshoot performance and data quality issues

• Drive an AI-first culture through internal playbooks and "golden-path" templates while measuring impact via DORA and SPACE metrics. • Manage AI costs through token budgeting and usage tracking alongside guardrails like PII redaction and audit logging. • Build and document reusable patterns for code generation, PRs, testing, and debugging to optimize the end-to-end developer lifecycle. • Conduct POCs and provide recommendations for AI tools based on ROI, technical merit, and stakeholder feedback. • Manage lightweight AWS infrastructure including API Gateways and LLM pipelines while integrating tools with CI/CD and GitLab.

• Design and build AI-powered enterprise solutions • Develop agentic frameworks, AI agents, and intelligent workflows • Architect and scale systems using Java, platform engineering, and DevOps practices • Integrate AI capabilities (LLMs, RAG, APIs) into existing platforms • Collaborate with stakeholders to drive practical AI adoption • Contribute to shaping AI direction in an evolving and ambiguous environment

• Operate and improve platform tools so product teams can ship reliably triaging tickets, fix build issues, and handling routine service requests (access, secrets, environment setup). • Maintain and extend self-service workflows (templates, golden paths) by updating docs, examples, and guardrails under guidance from senior engineers. • Perform day-to-day Kubernetes operations: deploy/update Helm charts, manage namespaces, diagnose rollout issues, and follow runbooks for incident response. • Support CI/CD pipelines (e.g., GitLab CI): keep pipelines green, add/adjust jobs, implement basic quality gates, and help teams adopt safer deploy strategies (blue/green, canary). • Monitor and operate the observability stack using Prometheus, Alert manager, and Thanos; maintain alert rules, dashboards, and SLO/SLA indicators; help reduce alert noise and improve signal quality. • Assist with service instrumentation across the core observability pillars—tracing, logging, and metrics—with hands-on OpenTelemetry usage (collectors/SDKs) and related telemetry tooling. • Contribute to and improve documentation: runbooks, FAQs, onboarding guides, and standard operating procedures. • Participate in an on-call rotation as needed with a well-defined escalation path; assist during incidents, post small fixes, and capture learnings in docs. • Help with cost- and performance-minded housekeeping: right-size workloads, prune unused resources, and automate routine tasks where appropriate.

• Design and develop analytics-ready datasets optimized for BI consumption • Build and maintain BI-focused data models (facts, dimensions, star/snowflake schemas) to support BI semantic models • Define, document, and govern business metrics and calculations • Develop transformations and analytical models using dbt and Python • Leverage existing SQL Server and AWS data warehouse data to create trusted analytical data sources • Write, debug, and maintain Python-based data transformation and analytics logic independently • Partner with BI and business teams to ensure accurate, consistent, and well-defined data structures • Analyze and reverse-engineer existing datasets or reports to diagnose data or metric inconsistencies • Ensure data quality, performance, scalability, and reliability of analytical models with minimal dependency on other engineers

• Execute SEO strategies (technical, on-page, off-page) • Plan & optimize paid campaigns for lead generation • Improve conversion rates and campaign ROI • Set up tracking, dashboards & monthly reports • Manage US clients independently and present insights

• Design and develop analytics-ready datasets optimized for BI consumption • Build and maintain BI-focused data models (facts, dimensions, star/snowflake schemas) to support BI semantic models • Define, document, and govern business metrics and calculations • Develop transformations and analytical models using dbt • Leverage existing SQL Server and AWS data warehouse data to create trusted analytical data sources • Partner with BI and business teams to ensure accurate, consistent, and well-defined data structures • Analyze and reverse-engineer existing datasets or reports to diagnose data or metric inconsistencies • Ensure data quality, performance, and scalability of analytical models