Persistent Systems is seeking a Data Analyst to join our team in our New York City headquarters. The Data Analyst will transform complex operational, financial, customer, product, and program data into accurate, timely, and actionable insights. This role will build trusted datasets, semantic models, dashboards, and analyses that help leaders understand performance, identify opportunities, manage risk, and make evidence-based decisions.
The ideal candidate is a disciplined problem solver and an effective "data translator" who can move comfortably between business questions and technical details. They combine strong SQL, data preparation, visualization, statistical reasoning, and stakeholder communication skills with a sharp eye for data quality and user experience.
Position Responsibilities
- Own analytical work from requirements discovery and source-data assessment through transformation, modeling, validation, visualization, delivery, and ongoing support
- Partner with leaders and subject-matter experts across Finance, Operations, Marketing, Sales, Product, and other functions to define key performance indicators (KPIs), reporting logic, and success measures
- Develop reliable, reusable analytics assets and clear documentation so that metrics, assumptions, transformations, and data lineage can be understood and maintained
- Apply statistical and analytical methods appropriate to the business question, communicate uncertainty and limitations, and distinguish correlation from evidence of causation
- Promote secure, governed, accessible, and responsible use of data while improving self-service analytics across the organization
- Design, build, and maintain intuitive dashboards, scorecards, semantic models, and recurring reports using Power BI as the primary platform and Tableau where appropriate
- Write, review, and optimize complex SQL queries across relational databases, cloud warehouses, and Lakehouse platforms; reconcile results to source systems and explain query logic
- Clean, profile, map, join, and transform structured and semi-structured data using Power Query, Python/pandas, spreadsheets, and related tools; design fact and dimension models using star-schema principles
- Build or contribute to repeatable extraction, transformation, and loading workflows using frameworks an