Data Analyst

Job Description Summary:

Key Skills: Strong SQL, Python (specially Pandas), Pyspark, Jupyter Notebook, Agile / Scrum / Jira / Confluence, Microsoft Excel, Exposure to any cloud (GCP / AWS / Azure)

Job Description:

Must-Have:

• 5 - 7 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.

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.