Company Name

PwC

Job Title

Data Engineer

Experience

0+ years of Experience

Location

Hyderabad, Bangalore, Kolkata,

Requirements

•  0+ years of experience in data engineering, working with Python and SQL.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud is preferred.
•  Familiarity with data visualization tools (e.g., Power BI, Tableau, QuickSight) is a plus.
•  Basic understanding of data modeling, ETL processes, and data warehousing concepts.
•  Strong analytical and problem-solving skills, with attention to detail.
• Bachelor’s degree in Computer Science, Data Science, Information Technology, or related
  fields.
•  Basic knowledge of cloud platforms and services is advantageous.
•  Strong communication skills and the ability to work in a team-oriented environment.

Rules and Responsibilities

•  Develop, optimize, and maintain data pipelines and workflows to ensure eƯicient data integration from multiple sources.
• Use Python and SQL to design and implement scalable data processing solutions.
• Ensure data quality and consistency throughout data transformation and storage
  processes.
• Collaborate with data architects and senior engineers to build data solutions that meet
  business and technical requirements.
• Work with cloud platforms (e.g., AWS, Azure, or Google Cloud) to deploy and maintain data
  solutions.
• Support the migration of on-premise data infrastructure to the cloud environment when
  needed.
• Assist in implementing cloud-based data storage solutions, such as data lakes and data
  warehouses.
• Data Visualization: Provide data to business stakeholders for visualizations using tools such as Power BI, Tableau, or QuickSight. Collaborate with analysts to understand their data needs and optimize data structures for reporting.
• Collaboration and Support:  Work closely with cross-functional teams, including data scientists and business analysts, to support data-driven decision-making.  Troubleshoot and resolve issues in the data pipeline and ensure timely data delivery. Document processes, data flows, and infrastructure for team knowledge sharing.