Specialty/Competency: Data, Analytics & AI
Industry/Sector: EUR X-Sector
Time Type: Full time
Travel Requirements: Up to 80%
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 decision-making 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.
Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e. g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
Minimum Degree Required
Bachelor's Degree
Required Field(s) of Study
Management Information Systems,Computer and Information Science,Systems Engineering,Electrical Engineering,Chemical Engineering,Industrial Engineering,Mathematics,Statistics,Mathematical Statistics
Minimum Year(s) of Experience
4 year(s)
Preferred Qualifications
Certification(s) Preferred
Certification in Cloud Platforms [e. g. , AWS Certified Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Certified: Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is a plus
Preferred Knowledge/Skills
Demonstrates thorough abilities and/or success in one or many of the following areas:
Design and implement comprehensive data architecture strategies that meet current and future business needs;
Develop and document data models, data flow diagrams, and data architecture guidelines;
Ensure data architecture is compliant with data governance and data security policies;
Collaborate with business stakeholders to understand their data requirements and translate them into technical solutions;
Evaluate and recommend new data technologies and tools to enhance data architecture;
Evaluate data and technology architecture options and build case for change across architecture principles like Security, Reliability, Scalability, Maintainability, Automation and Cost management;
Lead and drive data strategy engagements providing thought leadership to client and internal tech stakeholders and leadership;
Develop leading practices and perspectives for Data Engineering, Data Science, and Data Governance and Data Management
Lead the implementation of cloud-based solutions, ensuring they meet the specified requirements and best practices across batch, real-time, structured, semi-structured and unstructured datasets;
Architect, design, build and optimize ETL/ELT pipelines for data ingestion, processing, and storage;
Develop and deploy scalable data storage solutions using AWS, Azure and GCP services such as S3, Redshift, RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc. ;
Architect & Implement data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services;
Architect, Design and implement data warehouses and data lakes, ensuring data is organized and accessible;
Develop frameworks for monitoring and troubleshooting data pipelines, data warehouses and workflows to ensure data quality, system reliability, performance and cost management;
Architect and oversee implementation of IAM roles and policies to manage access and permissions within AWS, Azure, GCP;
Develop automation strategies leveraging AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments;
Architect and implement services using AWS, Azure and GCP DevOps services to build and deploy DevOps pipelines;
Develop data security best practices using AWS, Azure, GCP, Snowflake or Databricks;
Optimize Cloud resources for cost, performance, and scalability;
Possess proficiency in SQL and experience with relational databases;
Proficient in programming languages such as Python, Java, or Scala;
Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus;
Experience with machine learning and data science workflows is a plus;
Knowledge of data governance and data security best practices;
Demonstrate proven analytical, problem-solving, and communication skill; and,
Possess ability to work independently and as part of a team in a fast-paced environment.
Demonstrates thorough abilities with, and/or a proven record of success directing efforts in the following areas:
Apply modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures;
Collaborate and contribute as a team member by understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback;
Prioritize and handle multiple tasks, research and analyze pertinent client, industry and technical matters, utilize problem-solving skills, and communica.
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