Data Engineer - Manager

About the role

PwC's data and analytics engineering team focuses on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They transform raw data into actionable insights, enabling informed decision-making and business growth.

Responsibilities

• Design and implement thorough data architecture strategies
• Lead the development of data models
• Achieve compliance with data governance policies
• Collaborate with business stakeholders to translate data requirements into technical solutions
• Evaluate and recommend new data technologies and tools to enhance data architecture
• Build, maintain, and improve ETL/ELT pipelines for data ingestion, processing, and storage
• Manage data warehouses and data lakes, ensuring data is organized and accessible
• Implement data integration solutions using AWS, Azure, and GCP services
• Maintain and improve data quality rules using DQ tools and ETL/ELT tools
• Deploy scalable data storage solutions using AWS, Azure, and GCP services
• Implement data security practices using AWS, Azure, GCP, Snowflake, and Databricks
• Optimize cloud resources for cost, performance, and scalability
• Proficient in SQL and relational databases
• Experience with programming languages such as Python, Java, or Scala
• Familiarity with big data technologies like Hadoop, Spark, or Kafka
• Knowledge of data governance and data security practices
• Strong analytical, problem-solving, and communication skills
• Ability to work independently and as part of a team in a fast-paced environment
• Proficiency in modern cloud-based technology skills and emerging trends
• Collaborate and contribute as a team member, understanding personal and team roles
• Coach and collaborate with associates who assist with this work

Requirements

• Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics
• 5 years of experience

Qualifications

• Designing and implementing thorough data architecture strategies that meet current and future business needs
• Developing and documenting data models, data flow diagrams, and data architecture guidelines
• Verifying data architecture is compliant with data governance and data security policies
• Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions
• Evaluating and recommending new data technologies and tools to enhance data architecture
• Building, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage
• Managing data warehouses and data lakes, ensuring data is organized and accessible
• Monitoring and troubleshooting data pipelines, data warehouses, and workflows to verify data quality, system reliability, performance, and cost management
• Implementing IAM roles and policies to manage access and permissions within AWS, Azure, and GCP
• Using AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments
• Using AWS, Azure, and GCP DevOps services to build and deploy DevOps pipelines
• Implementing data security practices using AWS, Azure, GCP, Snowflake, or Databricks
• Improving cloud resources for cost, performance, and scalability
• Proficiency in SQL and experience with relational databases
• Experience with programming languages such as Python, Java, or Scala
• Familiarity with big data technologies like Hadoop, Spark, or Kafka
• Knowledge of data governance and data security practices
• Demonstrated analytical, problem-solving, and communication skills
• Ability to work independently and as part of a team in a fast-paced environment
• Proficiency in modern cloud-based technology skills and emerging trends
• Collaborate and contribute as a team member, understanding personal and team roles
• Coach and collaborate with associates who assist with this work