Key Skills: Power BI, SQL, DAX, Data Modelling, Tableau, Dashboard, Data Visualization, ETL/ELT.
Proven experience building enterprise-scale analytics solutions and dashboards.
Expert-level proficiency in Power BI including DAX measures, calculated columns, Power Query (M), and data modeling.
Strong understanding of data visualization best practices, chart selection, dashboard UX, and storytelling with data.
Advanced SQL skills for analytical queries, data exploration, and validation.
Experience designing semantic layers and business-friendly data models (star schema, metrics layers).
Strong knowledge of analytics platforms such as Power BI or Tableau or Looker, or similar tools and their integration patterns.
Understanding of metrics and KPI frameworks - ability to translate business requirements into measurable metrics.
Experience collaborating with data engineering teams on end-to-end pipelines: understanding source to target mappings, ETL/ELT pipelines, and refresh/orchestration patterns.
Experience with data at scale and performance optimization techniques for large datasets.
Experience with AI-powered analytics tools and using AI to accelerate dashboard development and insights generation (Preferred).
Knowledge of Python for advanced data preparation, custom calculations, or statistical analysis (Preferred).
Familiarity with embedded analytics patterns - integrating dashboards into applications via APIs or JavaScript SDKs (Preferred).
Experience with ERP/CRM analytics - SAP BI/BW, Salesforce Einstein Analytics, Workday Reporting (Preferred).
Knowledge of real-time dashboards and streaming data visualization (Preferred).
Domain expertise in Industrial Operations, Customer Service, ITSM, or SecOps analytics (Preferred).
Qualifications:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
Job Description:
Design and develop production-grade dashboards, KPIs, and metrics using Power BI (DAX, Power Query, data modeling) or Tableau or Looker.
Create semantic layers and business-friendly data models that enable self-service analytics for end users.
Define and implement key business metrics and KPIs in collaboration with product owners and domain experts.
Build interactive visualizations that integrate with ServiceNow platform and drive insight-to-action workflows.
Optimize dashboard performance, implement row-level security, and ensure scalability for enterprise deployments.
Design and implement upstream data preparation flows (Power Query, dataflows, SQL/dbt layers) to shape data for dashboards, reducing manual dependence on Data Engineers for every change.
Perform data profiling and validation, define data quality rules for key KPIs, and work with Data Engineers to embed these checks into pipelines feeding BI semantic models.
Work closely with Data Engineers and Data Modelers to understand data structures and ensure accurate metric calculations.