Data And Analytics Engineering ManagerAt 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.
Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm.
You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: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.As part of the Data and Analytics Engineering team you can design and implement thorough data architecture strategies that meet current and future business needs.
As a Manager you can lead the development of data models, support compliance with data governance policies, and collaborate with business stakeholders to translate data requirements into technical solutions. You can also build and enhance ETL/ELT pipelines, manage data warehouses and data lakes, and implement data security practices.Responsibilities:Design and implement thorough data architecture strategiesLead the development of data modelsAchieve compliance with data governance policiesCollaborate with business stakeholders to translate data requirementsBuild and enhance ETL/ELT pipelinesManage data warehouses and data lakesImplement data security leading practicesFoster a culture of data-driven decision makingWhat You Must Have:Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics5 years of experienceWhat Sets You Apart: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)Designing and implementing thorough data architecture strategies that meet the current and future business needsDeveloping and documenting data models, data flow diagrams, and data architecture guidelinesVerifying data architecture is compliant with data governance and data security policiesCollaborating with business stakeholders to understand their data requirements and translate them into technical solutionsEvaluating and recommending new data technologies and tools to enhance data architectureBuilding, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage across batch and real-time data processingBuilding, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT toolsDeveloping 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 servicesDesigning and managing data warehouses and data lakes, verifying data is organized and accessibleMonitoring and troubleshooting data pipelines, data warehouses and workflows to verify data quality, system reliability, performance and cost managementImplementing IAM roles and policies to manage access and permissions within AWS, Azure, GCPUse AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deploymentsUse AWS, Azure and GCP DevOps services to build and deploy DevOps pipelinesImplementing data security practices using AWS, Azure, GCP, Snowflake or DatabricksImproving Cloud resources for cost, performance, and scalabilityProficiency in SQL and experience with relational databasesProficient in programming languages such as Python, Java, or ScalaFamiliarity with big data technologies like Hadoop, Spark, or Kafka is a plusExperience with machine learning and data science workflows is a plusKnowledge of data governance and data security practicesDemonstrating analytical, problem-solving, and communication skillsHaving the ability to work independently and as part of a team in a fast-paced environmentApplying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architecturesCollaborating 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 feedbackPrioritizing 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 environmentCoaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performanceTravel Requirements: Up to 60%