Job
Description
Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decisionmaking and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purposeled and valuesdriven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . & Summary A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Design, develop and maintain data warehouse solutions using Snowflake, while ensuring data quality, accuracy, and consistency. Knowledge of SQL language and stored procedures SQL performance measuring, query tuning, and database tuning Data warehousing concepts, data modeling, metadata management Create and maintain stored procedures and SQL scripts to support ETL processes and data transformations. Performance tuning and setting up resource monitors Snowflake modeling roles, databases, schemas Core Snowflake concepts Snowpipe, tasks, streams, dynamic tables, etc. Write, optimize, and troubleshoot SQL queries within the Snowflake environment. Integrate Snowflake with various data sources and thirdparty tools. Proficient in SQL and familiar with ETL processes Handson experience with Snowflake features like Time Travel and ZeroCopy Cloning Managing sets of XML, JSON, and CSV from disparate sources Mandatory skill sets Integration with thirdparty tools Data Build Tool(dbt) Coding in languages like Python Hadoop, Spark, and other warehousing tools Preferred skill sets Integration with thirdparty tools Data Build Tool(dbt) Coding in languages like Python Hadoop, Spark, and other warehousing tools SnowPro Certification Years of experience required 3 7 Education qualification B.Tech / M.Tech / MBA / MCA Education Degrees/Field of Study required Master of Engineering, Master of Business Administration, Bachelor of Engineering Degrees/Field of Study preferred Required Skills PySpark Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation, Data Validation {+ 18 more} No
