Scientific Project Consultant at Novartis ensuring scientific rigor in early development of biologics and cell therapies. Providing strategic guidance and leadership across projects for timely execution.
About the role
- Director of Information Systems overseeing the design and optimization of enterprise data and applications at Blackstone Industrial. Leading a team to deliver scalable decision-support tools across multiple business domains.
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).
Benefits
- Experience with dbt, Airflow/Prefect, Fivetran/Matillion, Kafka/EventBridge, Snowflake/BigQuery/Azure Synapse, PostgreSQL/SQL Server, and Power Platform (Power Apps/Automate).
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