Data Architect- Manager

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.

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.

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

5 year(s)

Preferred Qualifications

Demonstrates 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;

• Strong 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;

• Strong analytical, problem-solving, and communication skill; and,

• Ability to work independently and as part of a team in a fast-paced environment.

Demonstrates thought leader-level abilities with, and/or a proven record of success directing efforts in the following areas:

• 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; and,

• Research emerging trends, analyzing publications, and adopting modern technologi.