Data Analyst

Total Exp - 7 to 9 Years

Location - Pune

Key Skills - Python SQL Pandas Numpy Pyspark

Technical:

• Analyze large datasets to derive actionable insights and support decision-making processes. Proven experience in data analytics and working with large datasets.
• Proficiency in Python, including libraries such as Pandas and Numpy for data manipulation.
• Strong SQL skills for querying and managing databases.
• Experience with PySpark for large-scale data processing.
• Basic understanding of Hadoop and its ecosystem. Familiarity with data engineering concepts and best practices.
• Knowledge of data modeling, including schemas, normalization, and denormalization techniques. Understanding of data centralization, cardinality, and data quality principles.
• Develop and maintain data pipelines using PySpark and other data processing tools.
• Implement data models and schemas to organize and optimize data storage and retrieval.
• Collaborate with data engineers to centralize and manage data assets.
• Utilize CI/CD pipelines to streamline data deployment and maintain continuous integration.

Functional:

• Determining, creating, and implementing internal process improvements, such as redesigning infrastructure for increased scalability, improving data delivery, and automating manual procedures.
• Building analytical tools that make use of the data flow and offer a practical understanding of crucial company performance indicators like operational effectiveness and customer acquisition.
• Helping stakeholders, including the data, design, product, and executive teams, with technical data difficulties.
• Working on data-related technical challenges while collaborating with stakeholders, including the Executive, Product, Data, and Design teams, to support their data infrastructure needs.
• Remaining up-to-date with developments in technology and industry norms can help you to produce higher-quality results.