Data Engineer - Manager

PwC is a leading advisory services firm focusing on data and analytics engineering. The Data Engineer - Manager will design and develop data solutions, manage data infrastructure, and lead a team to deliver quality data insights for clients.

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
• Build and enhance ETL/ELT pipelines
• Manage data warehouses and data lakes
• Implement data security leading practices
• Foster a culture of data-driven decision making

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
• Analyse and identify the linkages and interactions between the component parts of an entire system
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables
• Develop skills outside your comfort zone, and encourage others to do the same
• Effectively mentor others
• Use the review of work as an opportunity to deepen the expertise of team members
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate
• 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
• 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
• Build and enhance ETL/ELT pipelines
• Manage data warehouses and data lakes
• Implement data security leading practices
• Foster a culture of data-driven decision making
• 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 across batch and real-time data processing
• Building, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT tools
• Developing and deploying scalable data storage solutions using AWS, Azure and GCP services such as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc
• Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services
• Designing and managing data warehouses and data lakes, verifying 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, GCP
• Use AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments
• Use 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
• Proficient in programming languages such as Python, Java, or Scala
• Knowledge of data governance and data security practices
• Demonstrating analytical, problem-solving, and communication skills
• Having the ability to work independently and as part of a team in a fast-paced environment
• Applying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures
• Collaborating and contributing as a team member: understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback
• Prioritizing and handling multiple tasks, researching and analyzing pertinent client, industry and technical matters, utilizing problem-solving skills, and communicating effectively in written and verbal formats to various audiences (including various levels of management and external clients) in a professional business environment
• Coaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performance
• Certification in Cloud Platforms [e.g., AWS Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus
• Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus
• Experience with machine learning and data science workflows is a plus