Manager - Data Architect - D&A Advisory - Mumbai

As a Big Data Architect cum Data Engineer at PwC, your primary focus will be on designing and implementing scalable big data architectures and solutions using advanced technologies such as PySpark, SparkSQL, and Databricks on Azure or AWS. You will play a crucial role in building robust data models, developing ETL pipelines, ensuring data quality, and establishing data governance principles. Your expertise will be essential in driving project success through effective collaboration with cross-functional teams and leveraging industry knowledge in banking, insurance, and pharma to tailor data solutions. Additionally, you will stay updated with industry trends and innovations to proactively implement cutting-edge technologies and methodologies, while documenting technical solutions and design specifications clearly and concisely.

- Design and implement scalable big data architectures and solutions utilizing PySpark, SparkSQL, and Databricks on Azure or AWS. - Build robust data models and maintain metadata-driven frameworks to optimize data processing and analytics. - Create and deploy sophisticated ETL pipelines using Azure Data Factory and other Azure-based tools. - Ensure seamless data flow from various sources to destinations including ADLS Gen 2. - Implement data quality checks and validation frameworks. - Establish and enforce data governance principles ensuring data security and compliance with industry standards and regulations. - Manage version control and deployment pipelines using Git and DevOps best practices. - Provide accurate effort estimation and manage project timelines effectively. - Collaborate with cross-functional teams to ensure aligned project goals and objectives. - Leverage industry knowledge in banking, insurance, and pharma to design tailor-made data solutions. - Stay updated with industry trends and innovations to proactively implement cutting-edge technologies and methodologies. - Facilitate discussions between technical and non-technical stakeholders to drive project success. - Document technical solutions and design specifications clearly and concisely. Qualifications: - Bachelor's degree in computer science, Engineering, or a related field. Master's Degree preferred. - 8+ years of experience in big data architecture and engineering. - Extensive experience with PySpark, SparkSQL, and Databricks on Azure. - Proficient in using Azure Data Lake Storage Gen 2, Azure Data Factory, Azure Event Hub, Synapse. - Strong experience in data modeling, metadata frameworks, and effort estimation. - Experience of DevSecOps practices with proficiency in Git. - Demonstrated experience in implementing data quality, data security, and data governance measures. - Industry experience in banking, insurance, or pharma is a significant plus. - Excellent communication skills, capable of articulating complex technical concepts to diverse audiences. - Certification in Azure, Databricks or related Cloud technologies is a must. - Familiarity with machine learning frameworks and data science methodologies would be preferred.

As a Big Data Architect cum Data Engineer at PwC, your primary focus will be on designing and implementing scalable big data architectures and solutions using advanced technologies such as PySpark, SparkSQL, and Databricks on Azure or AWS. You will play a crucial role in building robust data models, developing ETL pipelines, ensuring data quality, and establishing data governance principles. Your expertise will be essential in driving project success through effective collaboration with cross-functional teams and leveraging industry knowledge in banking, insurance, and pharma to tailor data solutions. Additionally, you will stay updated with industry trends and innovations to proactively implement cutting-edge technologies and methodologies, while documenting technical solutions and design specifications clearly and concisely.

- Design and implement scalable big data architectures and solutions utilizing PySpark, SparkSQL, and Databricks on Azure or AWS. - Build robust data models and maintain metadata-driven frameworks to optimize data processing and analytics. - Create and deploy sophisticated ETL pipelines using Azure Data Factory and other Azure-based tools. - Ensure seamless data flow from various sources to destinations including ADLS Gen 2. - Implement data quality checks and validation frameworks. - Establish and enforce data governance principles ensuring data security and compliance with industry standards and regulations. - Manage version control and deployment pipelines using Git and DevOps best practices. - Provide accurate effort estimation and manage project timelines effectively. - Collaborate with cross-functional teams to ensure aligned project goals and objectives. - Leverage industry knowledge in banking, insurance, and pharma to design tailor-made data solutions. - Stay updated with industry tr