DATA ANALYST
Job Description:
Key Skills: Strong Sql, Python, Pyspark, Jupyter Notebook, Agile / Scrum / Jira / Confluence, Microsoft Excel, Exposure to any cloud (GCP / AWS / Azure)
Must-Have:
- 4-6 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, Hive and Spark.
- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.
- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.
- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.
- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.
- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.
- Understanding of ER Diagram and Data Modeling concepts
- Exposure to Data quality validation
- Exposure to Data Management, Data Cleaning and Data Preparation
- Exposure to Data Schema analysis.
- Exposure to working in Agile framework.
- Excellent verbal and written communication skills.
Good To Have:
- BFSI Domain knowledge
- Data Visualization - Excel, Tableau, Power BI
- Exposure to Hadoop, Hive and ETL.
- Working knowledge of any cloud services like AWS or GCP or Azure.
- Any relevant certifications would be a plus.
Role & Responsibilities:
- Take complete responsibility for the sprint stories' execution.
- Understand the business requirements from the product/project stakeholders 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.
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