23 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Develop and maintain data pipelines across cloud and analytics platforms.
- Design data integration, transformation, validation, data modeling, and warehouse processes.
- Automate orchestration workflows using Apache Airflow, Azure Data Factory, or similar tools.
- Optimize queries, storage patterns, and database operations across Snowflake, Databricks, and other platforms.
- Translate client data requirements into technical designs and implementation plans.
- Troubleshoot data quality, pipeline, and platform issues and identify corrective actions.
- Review junior team members' deliverables and provide technical guidance.
- Apply data architecture, security, and anonymization practices in enterprise data environments.
- Evaluate emerging tools, methods, and platform capabilities for modernization initiatives.
Requirements
- Bachelor's degree or higher is required.
- At least four years of experience is required, including three or more years of relevant technical or technology experience.
- At least three years of hands-on experience building applications with Python is required.
- Strong programming skills in Python and proficiency in SQL and database management systems are required.
- Understanding of scalable Python application architecture, particularly for GenAI use cases, is required.
- Familiarity with Flask, FastAPI, cloud-native development patterns, REST APIs, microservices, and serverless functions is required.
- Experience deploying and managing containerized applications on Azure or AWS is required.
- Experience with Apache Spark or similar data processing frameworks is required.
- Strong proficiency in Git and knowledge of cloud CI/CD practices are required.
- English oral and written proficiency is required.
- Preferred fields of study include management information systems, computer and information science, systems engineering, electrical engineering, chemical engineering, industrial engineering, mathematics, statistics, and mathematical statistics.
- Preferred qualifications include coursework or internship exposure in data engineering and experience with Databricks, Snowflake, Azure Data Factory, Apache Airflow, data pipelines, data transformation, data quality, data modeling, query optimization, and client-facing workstreams.
Benefits
- The role is based at PwC Acceleration Center Bangalore and involves collaboration with global teams across geographies and jurisdictions.
- The employer highlights hands-on learning, cutting-edge tools, and an inclusive culture.
- Travel requirements are not specified.
Categories
Data Engineering
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.