01Responsibilities
Develop data visualizations, dashboards, and automated reporting solutions that improve visibility into KPIs, operational performance, and business outcomes.
Design, build, and maintain data pipelines, databases, and integrations that consolidate data from multiple systems and support reporting, analytics, and automation use cases.
Develop custom internal tools, scripts, and lightweight applications using technologies such as Python, JavaScript, SQL where appropriate.
Experience designing and deploying Power Apps (Canvas and/or ModelDriven Apps) integrated with Power BI, Dataverse, SharePoint, and enterprise data sources
Identify, evaluate, and implement AI-powered automation opportunities, including document processing, workflow automation, and decision-support solutions.
Support system integration efforts by connecting business software and data sources to enable smoother workflows and better access to information.
Partner with portfolio company stakeholders to understand business problems, define requirements, and translate them into technical specifications and deliverables.
Automate manual workflows to improve speed, accuracy, and scalability across functions such as operations, finance, commercial, and shared services.
Design and deliver both deterministic (rule-based, logic-driven) and probabilistic (statistical, forecasting, AI/ML) analytical solutions, selecting the appropriate approach based on business risk, cost and decision context.
Support projects involving web scraping, API-based data capture, and structured/unstructured data collection where needed.
Create and maintain documentation for solutions, including process flows, data definitions, technical specifications, and user guides.
Test, troubleshoot, and continuously improve delivered solutions to ensure reliability, usability, and business impact.
Build cost-aware solutions, prioritizing native Microsoft 365 capabilities (Power BI, Power Apps, Power Automate, SharePoint) where appropriate to minimize tooling costs.
Implement postdeployment monitoring for analytics and ML solutions, including data drift, performance degradation, and reliability checks, and recommend corrective actions as needed.
Education and Experience:
Education: Bachelors degree in engineering, computer science, information technology, data science, analytics, or a related field. Masters degree preferred.
Experience: Minimum 47 years of experience in analytics, business intelligence, automation, application development, data engineering, or related technical roles. Experience delivering business-facing tools and solutions for senior stakeholders is required.
Skills and Abilities:
Strong proficiency in Power BI or similar data visualization tools.
Strong proficiency in SQL and experience with relational databases, ETL/ELT processes, and data modeling.
Experience with Python and/or JavaScript for automation and custom tool development.
Experience building dashboards, automated reports, and KPI tracking solutions.
Familiarity with APIs, web scraping, and systems integration.
Exposure to AI/ML-enabled solutions, workflow automation, OCR, NLP, or .
