Senior Full Stack AI Engineer

Role Overview: As a Senior Associate Azure Data Engineer at PwC, you will focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights, enabling informed decision-making, and driving business growth. Specifically in data engineering, you will be responsible for designing and building data infrastructure and systems to facilitate efficient data processing and analysis. Key Responsibilities: - Design, implement, and maintain reliable and scalable data infrastructure - Write, deploy, and maintain software for building, integrating, managing, and quality-assuring data - Develop and deliver large-scale data ingestion, data processing, and data transformation projects on the Azure cloud - Mentor and share knowledge with the team, providing design reviews, discussions, and prototypes - Work with customers to deploy, manage, and audit standard processes for cloud products - Adhere to and advocate for software and data engineering standard processes such as Data Engineering pipelines, unit testing, monitoring, alerting, source control, code review, and documentation - Deploy secure and well-tested software meeting privacy and compliance requirements, and improve CI/CD pipeline - Ensure service reliability and follow site-reliability engineering standard processes, including on-call rotations for services maintenance - Design, build, deploy, and maintain infrastructure as code, containerizing server deployments - Collaborate with a cross-disciplinary team in a Scrum/Agile setup including data engineers, architects, software engineers, data scientists, data managers, and business partners Qualifications Required: - Bachelor or higher degree in computer science, engineering, information systems, or other quantitative fields - 6 to 9 years of relevant experience in building, productionizing, maintaining, and documenting reliable and scalable data infrastructure and data products in complex environments - Hands-on experience with Spark, SQL, pyspark, Python, Azure cloud platforms, Azure Data Factory, Azure Data Lake, Azure SQL DB, Synapse, Azure DevOps, and implementing large-scale distributed systems - Strong customer management skills, continuous learning attitude, and key behaviors including empathy, curiosity, creativity, and inclusivity (Note: Additional details about the company were not provided in the job description) Role Overview: As a Senior Associate Azure Data Engineer at PwC, you will focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights, enabling informed decision-making, and driving business growth. Specifically in data engineering, you will be responsible for designing and building data infrastructure and systems to facilitate efficient data processing and analysis. Key Responsibilities: - Design, implement, and maintain reliable and scalable data infrastructure - Write, deploy, and maintain software for building, integrating, managing, and quality-assuring data - Develop and deliver large-scale data ingestion, data processing, and data transformation projects on the Azure cloud - Mentor and share knowledge with the team, providing design reviews, discussions, and prototypes - Work with customers to deploy, manage, and audit standard processes for cloud products - Adhere to and advocate for software and data engineering standard processes such as Data Engineering pipelines, unit testing, monitoring, alerting, source control, code review, and documentation - Deploy secure and well-tested software meeting privacy and compliance requirements, and improve CI/CD pipeline - Ensure service reliability and follow site-reliability engineering standard processes, including on-call rotations for services maintenance - Design, build, deploy, and maintain infrastructure as code, containerizing server deployments - Collaborate with a cross-disciplinary team in a Scrum/Agile setup including data engineers, architects, software engineers, data scientists, data managers, and business partners Qualifications Required: - Bachelor or higher degree in computer science, engineering, information systems, or other quantitative fields - 6 to 9 years of relevant experience in building, productionizing, maintaining, and documenting reliable and scalable data infrastructure and data products in complex environments - Hands-on experience with Spark, SQL, pyspark, Python, Azure cloud platforms, Azure Data Factory, Azure Data Lake, Azure SQL DB, Synapse, Azure DevOps, and implementing large-scale distributed systems - Strong customer management skills, continuous learning attitude, and key behaviors including empathy, curiosity, creativity, and inclusivity (Note: Additional details about the company were not provided in the job description)