Director of Information Systems at Blackstone Industrial leading enterprise data strategy and optimization for critical rotating and static equipment. Combining engineering principles with information systems for scalable decision-support tools.
Responsibilities
Define, Develop and execute the enterprise data strategy and roadmap (12–24 months).
Stand up secure, scalable data pipelines (ELT/ETL), a data warehouse/lake, and semantic models (e.g., Snowflake/BigQuery).
Implement Power BI (governance, DAX models, shared datasets) and drive self-service analytics adoption across the business.
Build trusted datasets for Services (work orders, job cost, utilization, reliability KPIs), Parts Supply Chain (forecasting, inventory strategies, vendor performance), and Sales Enablement (pipeline health, pricing/margin analytics).
Apply industrial engineering techniques (queuing models, forecasting, utilization analysis, reliability KPIs) to operational datasets for optimization.
Establish data quality, lineage, access controls (RBAC), and change management.
Own and manage integrations between ERP/CMMS (e.g., Business Central, ViewPoint Spectrum), CRM (e.g., Salesforce), finance, and field/mobile apps (API-first, event-driven where practical).
Manage a small internal/contract engineering team to deliver custom applications (e.g., technician mobile workflows, quoting tools) with disciplined SDLC, CI/CD, and documentation.
Manage iPaaS/ELT, warehouse, BI, and development tool vendors.
Translate business questions into analytics and product increments and run a disciplined intake/prioritization process.
Deliver training and adoption programs for cross-functional teams.
Develop KPI catalogs, playbooks, and decision-support dashboards that directly impact efficiency, reliability, and margin.
Communicate progress, risks, and outcomes to leadership with measurable ROI.
Requirements
BS/MS in Computer Science, Information Systems, Industrial Engineering, or equivalent experience.
8–12+ years in industrial/systems, data/analytics, or information systems, including hands-on buildouts in a B2B/industrial or field-services context.
Proven experience building and operating production data platforms (pipelines + warehouse/lake + BI) end-to-end.
Strong proficiency in SQL (analytic/window functions, performance tuning) and Python (pandas/pyarrow, basic APIs/ETL).
Implemented Power BI at scale (dataset governance, DAX, RLS, deployment pipelines).
Delivered integrations across ERP/CMMS/CRM/Finance using modern integration patterns (REST/GraphQL, webhooks, message queues).
Team leadership experience (hiring/mentoring engineers, managing contractors, roadmap ownership, and cross-functional stakeholder management).
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