Job Summary

We are seeking a highly analytical and detail-oriented Senior Business Data Analyst / Analytics Engineer with strong expertise in SQL, ClickHouse, financial analytics, and data modeling. The ideal candidate will bridge the gap between Finance, Revenue Operations, and Technical teams by translating business requirements into scalable analytical solutions while ensuring data integrity, consistency, and performance.

Key Responsibilities

Advanced SQL & Analytics

- Develop and maintain complex SQL queries across large-scale datasets using ClickHouse or similar columnar databases.
- Create reusable query frameworks for recurring financial and operational reporting requirements.
- Perform data reconciliation across multiple systems to ensure consistency and accuracy of financial reporting.
- Optimize query performance and apply best practices for efficient data retrieval in ClickHouse environments.

Business Analysis & Requirements Gathering

- Collaborate with FP&A;, Revenue Operations, and business stakeholders to understand reporting and analytics needs.
- Translate business questions into structured data requirements and analytical solutions.
- Prepare functional specifications for new datasets, metrics, dashboards, and reporting layers.
- Document metric definitions, business logic, and data lineage to support long-term maintainability.

Data Modeling & KPI Governance

- Define, maintain, and govern KPI and metric calculations across finance, operations, and revenue reporting.
- Support hierarchical financial reporting structures, including parent-subsidiary relationships, revenue streams, adjustments, and allocations.




- Ensure consistent metric definitions across dashboards, reports, extracts, and backend datasets.
- Contribute to establishing and maintaining a single source of truth within the analytics ecosystem.

Analytics Engineering & Data Operations

- Work directly with ClickHouse databases and analytics-focused data models.
- Support and enhance Python-based analytics and reporting frameworks.
- Assist in maintaining and improving data pipelines feeding finance and operational dashboards.
- Recommend and implement improvements to data transformations and reporting workflows.

Data Validation & Quality Assurance

- Reconcile analytical outputs against source systems and financial records.
- Identify and investigate anomalies such as missing data, duplication, and aggregation inconsistencies.
- Develop repeatable validation checks, control totals, and variance analysis processes.
- Support regression testing and impact analysis for reporting and data model changes.

Dashboard & Reporting Support

- Support the development and enhancement of financial and operational dashboards.
- Improve KPI presentation, reporting usability, and data visualization clarity.
- Work closely with leadership and finance teams to refine reporting outputs and insights.





API & Data Integration Support

- Support API-based data ingestion and extraction processes.
- Troubleshoot and resolve basic integration issues between source systems and analytics platforms.
- Assist in maintaining connectivity between operational systems and the ClickHouse data warehouse.

Required Skills

- Strong SQL expertise with advanced query writing, joins, window functions, CTEs, and aggregations.
- Hands-on experience with ClickHouse or similar analytical databases.
- Strong understanding of financial reporting, FP&A; processes, and operational analytics.
- Experience in data modeling, KPI definition, and metric governance.
- Proficiency in Python for analytics, data processing, and troubleshooting.
- Strong analytical, problem-solving, and documentation skills.
- Experience with dashboarding and reporting tools.
- Understanding of APIs, data integrations, and ETL processes.

Preferred Qualifications

- Experience supporting Finance, Revenue Operations, or Business Intelligence teams.
- Familiarity with contemporary analytics engineering practices.
- Experience working in SaaS, technology, or data-driven organizations.
- Exposure to financial data reconciliation and audit controls.
- Knowledge of data warehousing concepts and analytics architecture.

Key Competencies

- Business Analysis
- Financial Data Analytics
- Data Modeling
- Analytics Engineering
- Stakeholder Management
- Problem Solving
- Data Governance
- Quality Assurance & ValidationRole & responsibilities

Preferred candidate profile

📌 Senior Business Data Analyst / Analytics Engineer (Chennai)
🏢 Prabal Information systems
📍 Chennai