A career within Financial Markets Business Advisory services, will provide you with the opportunity to contribute to a variety of audit, regulatory, valuation, and financial analyses services to design solutions that address our clients complex accounting and financial reporting challenges, as well as their broader business issues.
To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.
Responsibilities
As a Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:
- Develop new skills outside of comfort zone.
- Act to resolve issues which prevent the team working effectively.
- Coach others, recognise their strengths, and encourage them to take ownership of their personal development.
- Analyse complex ideas or proposals and build a range of meaningful recommendations.
- Use multiple sources of information including broader stakeholder views to develop solutions and recommendations.
- Address sub-standard work or work that does not meet firm's/client's expectations.
- Use data and insights to inform conclusions and support decision-making.
- Develop a point of view on key global trends, and how they impact clients.
- Manage a variety of viewpoints to build consensus and create positive outcomes for all parties.
- Simplify complex messages, highlighting and summarising key points.
- Uphold the firm's code of ethics and business conduct.
Role Overview
We are seeking an experienced Data Engineer - Manager to lead and oversee the development and deployment of scalable data solutions. The ideal candidate will possess strong expertise in Python, SQL, data modeling, and cloud platforms, with a deep understanding of data warehousing. Additionally, the role requires proficiency in PySpark, serverless computing, and machine learning/AI technologies. The Data Engineer - Manager will work closely with cross-functional teams, providing technical leadership and ensuring alignment with the organization's data strategies. Basic knowledge of data visualization tools like Power BI, Tableau, and QuickSight is preferred.
Key Responsibilities
Data Engineering Leadership:
Lead the design, development, and optimization of complex data pipelines and workflows, ensuring robust data integration and transformation.
Oversee the implementation of scalable data models and warehousing solutions to support large-scale data storage and analytics needs.
Provide hands-on technical leadership and mentorship to a team of data engineers, guiding them on best practices for coding, testing, and deployment.
Cloud Solutions & Data Warehousing
Architect and deploy cloud-based data solutions using platforms such as AWS, Azure, or Google Cloud.
Leverage cloud-native services and serverless computing (e.g., AWS Lambda, Azure Functions) to build cost-eicient, high-performance data processing systems.
Design and manage data warehousing solutions using cloud technologies, ensuring data I organized and easily accessible for analytical purposes.
PySpark & Big Data Processing
Utilize PySpark to process large datasets and implement eicient distributed data processing solutions.
Optimize data pipelines to handle both batch and streaming data for real-time insights.
Machine Learning & AI Integration
Collaborate with data scientists and machine learning teams to integrate predictive models into the data ecosystem.
Apply machine learning and AI techniques to automate and enhance data processing and analytics capabilities.
Data Visualization & Collaboration
Provide structured, clean data to business users for use in reporting and dashboards through tools like Power BI, Tableau, and QuickSight.
Partner with analytics teams to deliver actionable insights and drive data-driven decision- making across the organization.
Strategic Oversight & Stakeholder Engagement
Align data engineering initiatives with broader business goals, ensuring that data solutions meet evolving organizational needs.
Collaborate with senior leadership and cross-functional teams to define data strategies, roadmaps, and technical standards.
Continuously evaluate new data technologies, methodologies, and best practices to drive innovation and improvement in data processes.
Required Skills And Experience
8+ years of experience in data engineering, with strong proficiency in Python, SQL, and data modeling.
Expertise in cloud platforms (AWS, Azure, Google Cloud), including serverless computing and cloud-native services.
Strong knowledge of data warehousing, big data solutions, and distributed computing using
PySpark.
Hands-on experience with machine learning and AI tools, with the ability to integrate predictive models into data pipelines.
Basic familiarity with data visualization tools like Power BI, Tableau, or QuickSight.
Excellent leadership, problem-solving, and communication skills, with a proven track
record of managing and mentoring technical teams.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or related fields.
Proven experience in managing complex data projects and delivering high-quality, scalable data solutions.
Strong ability to collaborate with stakeholders and drive strategic data initiatives.
