Incanus Technologies is looking for a Senior Data Analyst who combines strong analytical thinking with hands-on expertise in SQL, Python, data visualization, and business problem-solving.

The role involves working closely with business, product, operations, finance, and engineering teams to analyze complex business problems, identify meaningful insights, and support data-driven decision-making.

You will work extensively with large and complex datasets, develop analytical frameworks, define and track business metrics, build dashboards and reports, conduct root-cause analysis, and translate data into actionable business recommendations.

This is a highly analytical role for someone who enjoys going beyond reporting to understand why something is happening, identify opportunities, and influence business decisions through data.

Key Responsibilities :

Data Analysis & Business Problem Solving :

- Analyze complex business problems using large datasets and identify trends, patterns, anomalies, and opportunities.

- Translate ambiguous business questions into structured analytical problems and define the right approach to solve them.

- Conduct exploratory and diagnostic analysis to understand key business drivers and performance trends.

- Conduct root-cause analysis and identify actionable recommendations for business and operational problems.

- Develop analytical frameworks to support business decisions, planning, and performance improvement.

- Partner with business and product stakeholders to understand objectives, define analytical requirements, and deliver relevant insights.

- Identify opportunities for process improvement, automation, and data-driven decision-making.

SQL & Data :

- Write complex and optimized SQL queries involving joins, subqueries, CTEs, window functions, aggregations, and data transformations.

- Extract, clean, transform, validate, and analyze data from multiple sources.

- Work with large and complex datasets across multiple databases and data sources.

- Perform data validation and reconciliation to ensure accuracy, consistency, and reliability of analysis.

- Understand database structures, relationships, data models, and data flows.

- Identify data quality issues and work with engineering and data teams to resolve them.

Python & Automation :

- Use Python for data analysis, exploratory analysis, data manipulation, statistical analysis, and automation.

- Build reusable analytical scripts and automate repetitive reporting and analysis workflows.

- Use Python libraries and tools commonly used for data analysis and visualization.

- Develop analytical solutions that improve the efficiency and scalability of data-driven processes.

Business Intelligence & Visualization :

- Build and maintain dashboards and reports to track business performance and key KPIs.

- Use BI tools such as Power BI, Tableau, or Looker to communicate insights effectively.

- Define meaningful metrics, KPIs, business rules, and measurement frameworks.

- Ensure dashboards and reporting accurately reflect business definitions and underlying data.

- Present complex analytical findings in a clear and actionable manner to business and senior stakeholders.

Stakeholder & Cross-functional Collaboration :

- Collaborate with Product, Engineering, Operations, Finance, and Business teams to solve cross-functional problems.

- Work closely with stakeholders to understand business context and ensure analysis addresses the right business questions.

- Translate complex data and analytical findings into clear business insights and recommendations.

- Present findings and recommendations to senior stakeholders.

- Partner with engineering and data teams to improve data availability, quality, and analytical infrastructure.

- Monitor the impact of recommendations and identify further opportunities for improvement.

Required Skills :

- Strong proficiency in SQL, including complex joins, subqueries, CTEs, window functions, aggregations, and data manipulation.

- Good proficiency in Python for data analysis, automation, and exploratory analysis.

- Strong analytical and problem-solving skills with the ability to structure ambiguous business problems.

- Strong understanding of business metrics, KPIs, and data-driven decision-making.

- Experience working with large datasets and deriving actionable insights.

- Strong understanding of data validation, data quality, and reconciliation.

- Experience with data visualization and dashboarding.

- Ability to communicate complex analytical findings clearly to non-technical stakeholders.

- Ability to work effectively with business, product, engineering, and other cross-functional teams.

Preferred Qualifications :

- Experience with BI tools such as Power BI, Tableau, or Looker.

- Understanding of databases, data models, and ETL/ELT processes and data pipelines.

- Familiarity with APIs, automation, or working with engineering and data engineering teams.

- Experience with statistical analysis, experimentation, forecasting, or analytical modeling.

- Experience in product analytics, business intelligence, operations analytics, or process optimization.

- Experience working with cloud data platforms or modern data stacks is a plus.

- Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.

Ideal Candidate :

We are looking for someone who :

- Can independently take a business problem from question to data to analysis to insight to recommendation.

- Is highly proficient in SQL and comfortable working with complex datasets.

- Can use Python to perform analysis and automate repetitive analytical workflows.

- Thinks beyond dashboards and reporting to understand the underlying business problem.

- Can identify the key drivers behind business performance rather than simply reporting metrics.

- Is comfortable working with ambiguity and independently defining the analytical approach.

- Can communicate complex findings clearly and turn analysis into actionable recommendations.

- Enjoys working closely with business and technical teams to solve real-world problems using data.

Experience :

- 1 - 4 years of experience as a Data Analyst, Business Analyst, Product Analyst, Business Intelligence Analyst, or similar analytical role.

- Candidates with strong technical expertise in SQL and Python, combined with demonstrated experience solving complex business problems through data, are encouraged to apply.