Data Analyst - IT

Must-Have:

- 4+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.

- Working knowledge / experience of Big Data frameworks like Hadoop and Spark.

- Working knowledge of any cloud services like AWS or GCP.

- Exposure to Data exploration: Ability to investigate and query data using HQL or SQL (Spark SQL)

- Exposure to Data quality validation

- Exposure to Data Management, Data Cleaning and Data Preparation

- Exposure to Data Schema analysis.

- Documentation: Technical Design documents, Business Requirements Documents understanding

- Excellent verbal and written communication skills.

Good To Have:

- Data Visualization (Power BI / Tableau)

- Good to have exposure to Creating Dashboards and Reports, Probability and Statistical knowledge, JIRA, Confluence, Statistical programming language like R, Machine Learning.

Role & Responsibilities:

- Take complete responsibility for the sprint stories' execution.

- Understand the business requirements and break the requirements into simpler stories and tasks and do the necessary mapping of the tasks to the logical model of the solutions.

- Mapping of business entities to technical attributes with the logic for transformation defined clearly.

- Be accountable for the delivery of the tasks in the defined timelines with good quality.

- Follow the processes for project execution and delivery.

- Follow agile methodology.

- Working with the team leads closely and contribute to the smooth delivery of the project.

- Understand/define the architecture and discuss the pros-cons of the same with the team.

- Involve in the brainstorming sessions and suggest improvements in the architecture/design.

- Working with other teams leads to getting the architecture/design reviewed.

- Keep all the stakeholders updated about the project, task status, risks and issues if any.

- Key Skills: Python, Pyspark, SQL, Microsoft Excel, Jupyter Notebook, Microsoft Excel