Data Analyst - Business Intelligence (2-5 yrs)

Key Responsibilities :

Data Analysis :

- Utilize data analysis tools (SQL, Tableau, Excel) to extract, clean, and transform API usage data.

- Conduct in-depth analysis of API usage patterns, performance metrics, and error logs.

- Identify trends, anomalies, and potential issues within API data.

API Lifecycle Management :

- Gain a solid understanding of API lifecycle management tools and platforms (Apigee, Postman).

- Leverage API governance principles and OpenAPI specifications to ensure data quality and consistency.

- Manage and maintain API metadata to facilitate efficient analysis and reporting.

Insight Generation :

- Interpret API usage data to uncover valuable insights into consumer behavior, product performance, and market trends.

- Develop data-driven recommendations to optimize API performance, enhance user experience, and drive business growth.

- Create compelling visualizations (dashboards, reports) to communicate findings effectively to technical and non-technical audiences.

Strategic Impact :

- Collaborate with cross-functional teams (product management, engineering, and business development) to align data insights with strategic objectives.

- Contribute to data-driven decision-making processes and support initiatives to improve API adoption and utilization.

Required Skills and Experience :

- Proven experience in data analysis and business intelligence.

- Strong proficiency in SQL, Tableau, and Excel.

- Familiarity with API lifecycle management tools and platforms (Apigee, Postman).

- Understanding of API governance, OpenAPI specifications, and metadata management.

- Ability to interpret complex data sets and extract meaningful insights.

- Excellent analytical and problem-solving skills.

- Strong communication and presentation skills.

- Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications :

- Experience with data visualization tools (Power BI, Looker).

- Knowledge of statistical analysis techniques.

- Experience working with large datasets and distributed computing frameworks (Hadoop, Spark).

- Understanding of cloud-based data platforms (AWS, GCP, Azure)