Data Engineer - Senior Manager

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.

Growing as a strategic advisor, you leverage your influence, expertise, and network to deliver quality results. You motivate and coach others, coming together to solve complex problems. As you increase in autonomy, you apply sound judgment, recognising when to take action and when to escalate. You are expected to solve through complexity, ask thoughtful questions, and clearly communicate how things fit together. Your ability to develop and sustain high performing, diverse, and inclusive teams, and your commitment to excellence, contributes to the success of our Firm.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Craft and convey clear, impactful and engaging messages that tell a holistic story.
• Apply systems thinking to identify underlying problems and/or opportunities.
• Validate outcomes with clients, share alternative perspectives, and act on client feedback.
• Direct the team through complexity, demonstrating composure through ambiguous, challenging and uncertain situations.
• Deepen and evolve your expertise with a focus on staying relevant.
• Initiate open and honest coaching conversations at all levels.
• Make difficult decisions and take action to resolve issues hindering team effectiveness.
• Model 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 design and implement thorough data architecture strategies that meet current and future business needs. As a Senior Manager you lead large projects, innovate processes, and maintain operational excellence while interacting with clients at a strategic level to drive project success. You also be responsible for developing and documenting data models, data flow diagrams, and data architecture guidelines, maintaining compliance with data governance and data security policies, and collaborating with business stakeholders to translate their data requirements into technical solutions.

Responsibilities

- Design and implement thorough data architecture strategies

- Lead large-scale projects and innovate processes

- Maintain operational excellence and client interactions

- Develop and document data models and data flow diagrams

- Adhere to data governance and security policies

- Collaborate with business stakeholders to translate data requirements into technical solutions

- Drive project success through strategic advising and problem-solving

- Foster a diverse and inclusive team environment

What You Must Have

- Bachelor's Degree

- 8 years of experience

What 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, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is a plus

- Designing and implementing thorough data architecture strategies

- Developing and documenting data models and data flow diagrams

- Maintaining data architecture compliance with governance and security policies

- Collaborating with stakeholders to translate data requirements into solutions

- Evaluating and recommending new data technologies and tools

- Leading data strategy engagements providing thought leadership

- Developing leading practices for Data Engineering, Data Science, and Data Governance

- Architecting and implementing cloud-based solutions meeting industry standards