Associate Process Manager

1. Analyze business and customer datasets to identify trends, patterns, opportunities, and key performance drivers.
2. Develop, maintain, and enhance interactive dashboards and reports using Power BI and/or Tableau.
3. Translate business requirements into meaningful KPIs, analytical solutions, dashboards, and reporting frameworks.
4. Perform ad-hoc analysis, data deep dives, and root-cause analysis to support business decision-making.
5. Prepare clear and actionable insights using effective data visualization and storytelling techniques.
6. Validate data accuracy, consistency, and completeness across reports and analytical outputs.
7. Collaborate with business, technology, and data teams to understand requirements and deliver analytical solutions.
8. Document KPI definitions, analytical methodologies, assumptions, and reporting logic to ensure consistency and reuse.

Must Have Skills

Strong proficiency in SQL, including joins, CTEs, aggregations, subqueries, and window functions.
Strong hands-on experience with Power BI and/or Tableau for dashboard development and data visualization.
Strong Excel skills, including advanced formulas, pivot tables, lookups, and data analysis.
Strong analytical and problem-solving skills with the ability to investigate and interpret complex datasets.
Ability to translate business requirements into measurable KPIs, reports, and analytical solutions.
Good understanding of data quality, validation, and basic data modeling concepts.
Ability to communicate analytical findings clearly to technical and non-technical stakeholders.

Good To Have Skills

Python/Pandas for data analysis, automation, and data preparation.
Experience with cloud data platforms such as Snowflake, BigQuery, Databricks, Azure, or AWS.
Understanding of statistical concepts such as hypothesis testing, correlation, regression, A/B testing, and confidence intervals.
Experience with Git/GitHub or other version-control tools.
Experience working with large-scale datasets and analytical data models.
AI / GenAI
Experience using Generative AI / LLM tools for data exploration, SQL generation, analysis, documentation, or workflow automation.
Familiarity with prompt engineering and responsible use of AI in analytics.
Exposure to AI-assisted BI, natural-language analytics, or automated insight generation.