The Role & Scope

As a Senior Data Analyst, you will transform complex, raw datasets into actionable insights that drive strategic business decisions. You will bridge the gap between business stakeholders and technical teams, leading data modeling efforts, optimizing complex queries, building Python-based automation, and ensuring top-tier data quality and governance across the organization.

Key Responsibilities

- Analyze large, complex datasets to identify critical trends, patterns, and anomalies; translate findings into executive-level business recommendations.
- Design, implement, and maintain Conceptual (CDM), Logical (LDM), and Physical (PDM) data models utilizing enterprise modeling tools.
- Write, tune, and optimize complex SQL queries, CTEs, and stored procedures for data extraction, transformation, and large-scale reporting.
- Conduct end-to-end data validation, profiling, and root-cause analysis to troubleshoot data anomalies and ensure continuous data consistency.
- Develop reusable, modular Python scripts to automate routine analytical workflows, data quality checks, and complex data processing.
- Partner directly with business leaders and engineering teams to translate business requirements into technical data solutions and impact analysis.




- Create and maintain comprehensive documentation for data architecture, business logic, and lineage while promoting data governance best practices.

Required Skills & Qualifications
- 5+ years of hands-on experience in data analysis, data modeling, and business intelligence within enterprise environments.
- Expertise in writing complex joins, window functions, CTEs, stored procedures, and query performance tuning.
- Deep theoretical and practical knowledge of CDM, LDM, and PDM development using tools like ERwin, ER/Studio, or Oracle SQL Developer Data Modeler.
- Strong practical experience using Python for advanced analytics, profiling, and automation (Pandas, NumPy, SQLAlchemy).
- Strong grasp of relational database management systems (RDBMS) and up-to-date data warehousing principles.
- Proven track record in data cleansing, root-cause analysis, and defining data quality metrics.

Preferred Qualifications
- Experience mentoring junior analysts or leading technical scoping for analytics projects.
- Exposure to cloud data platforms (e.g., Snowflake, BigQuery, AWS Redshift).
- Understanding of modern CI/CD practices for analytics code and automated testing.

📌 Senior Data Analyst (Pune)
🏢 Indexnine
📍 Pune