Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
AssociateJob Description & 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.To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.
As an Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:
Job Description: GenAI Data Engineer - Associate
PwC US - Acceleration Center is seeking an enthusiastic and emerging GenAI Data Engineer to join our team at the Associate level. This role is ideal for individuals passionate about data engineering and eager to develop their skills in GenAI technologies. As an Associate GenAI Data Engineer, you will contribute to developing and maintaining data pipelines, implementing machine learning models, and optimizing data infrastructure for our GenAI projects under the guidance of more experienced team members.
Responsibilities:
Assist in the design, development, and maintenance of data pipelines and ETL processes for GenAI projects.
Work closely with data scientists and software engineers to support the implementation of machine learning models and algorithms.
Help optimize data infrastructure and storage solutions to ensure efficient data processing.
Gain experience with event-driven architectures to enable real-time data processing and analysis.
Learn and assist with containerization technologies like Kubernetes and Docker for deployment and scalability.
Support the development and maintenance of data lakes for managing large volumes of structured and unstructured data.
Contribute to the integration of LLM frameworks (such as Langchain and Semantic Kernel) for advanced language processing and analysis.
Collaborate with cross-functional teams to support the design and implementation of solution architectures for GenAI projects.
Utilize cloud computing platforms such as Azure or AWS under supervision for data processing, storage, and deployment.
Participate in monitoring and troubleshooting of data pipelines and systems to ensure smooth operations.
Stay informed about the latest advancements in GenAI technologies and assist in recommending innovative solutions to enhance data engineering processes.
Engage with cross-functional teams to help understand business requirements and contribute to translating them into technical solutions.
Assist in documenting data engineering processes, methodologies, and best practices.
Requirements:
Bachelorβs degree in Computer Science, Data Science, or a related field.
1-3 years of relevant experience, ideally with some exposure to GenAI projects.
Basic programming skills in Python.
Familiarity with data processing frameworks like Apache Spark or similar.
Understanding of SQL and basic database management systems.
Some knowledge of event-driven architectures and real-time data processing.
Exposure to containerization technologies like Kubernetes and Docker.
Awareness of data lakes and basic data lake management principles.
Some familiarity with LLM frameworks such as Langchain and Semantic Kernel.
Experience with cloud computing platforms such as Azure or AWS is a plus.
Strong analytical and problem-solving skills.
Good communication and collaboration abilities.
Ability to work in a fast-paced and dynamic environment.
Nice to Have Skills:
Exposure to additional technologies such as Databricks, Azure AI Search, Azure OpenAI, Azure Event Hub, Azure Data Lake Storage, AWS Open Search, AWS Bedrock, AWS Event Bridge, AWS S3, Azure Key Vault,DataDog, and Splunk.
If you are early in your data engineering career and enthusiastic about GenAI technologies, join PwC US - Acceleration Center as an Associate GenAI Data Engineer. Here, you will develop your skills and contribute to innovative projects in a supportive and collaborative work environment.
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