Assurance Risk Modeling Services Data Engineer Manager

Industry/Sector

Specialism

Management Level

Job Description & Summary

Enhancing your leadership style you motivate develop and inspire others to deliver quality. You are responsible for coaching leveraging team members 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 Firms code of conduct and independence requirements.

Role Overview:
We are seeking an experienced Data Engineer - Manager to lead and oversee the development anddeployment of scalable data solutions. The ideal candidate will possess strong expertise in PythonSQL data modeling and cloud platforms with a deep understanding of data warehousing.
Additionally the role requires proficiency in PySpark serverless computing and machinelearning/AI technologies. The Data Engineer - Manager will work closely with cross-functionalteams providing technical leadership and ensuring alignment with the organizations datastrategies. Basic knowledge of data visualization tools like Power BI Tableau and QuickSight ispreferred.
Key Responsibilities:
Data Engineering Leadership:

• Lead the design development and optimization of complex data pipelines and workflowsensuring robust data integration and transformation.
• Oversee the implementation of scalable data models and warehousing solutions to supportlarge-scale data storage and analytics needs.
• Provide hands-on technical leadership and mentorship to a team of data engineers guidingthem on best practices for coding testing and Solutions & Data Warehousing:
• Architect and deploy cloud-based data solutions using platforms such as AWS Azure orGoogle Cloud.
• Leverage cloud-native services and serverless computing (e.g. AWS Lambda AzureFunctions) to build cost-eƯicient high-performance data processing systems.
• Design and manage data warehousing solutions using cloud technologies ensuring data isorganized and easily accessible for analytical purposes.

PySpark & Big Data Processing:

• Utilize PySpark to process large datasets and implement eƯicient distributed dataprocessing solutions.
• Optimize data pipelines to handle both batch and streaming data for real-time Learning & AI Integration:
• Collaborate with data scientists and machine learning teams to integrate predictive modelsinto the data ecosystem.
• Apply machine learning and AI techniques to automate and enhance data processing andanalytics capabilities.

Data Visualization & Collaboration:

• Provide structured clean data to business users for use in reporting and dashboardsthrough tools like Power BI Tableau and QuickSight.
• Partner with analytics teams to deliver actionable insights and drive data-driven decisionmaking across the organization.

Strategic Oversight & Stakeholder Engagement:

• Align data engineering initiatives with broader business goals ensuring that data solutionsmeet evolving organizational needs.
• Collaborate with senior leadership and cross-functional teams to define data strategiesroadmaps and technical standards.
• Continuously evaluate new data technologies methodologies and best practices to driveinnovation and improvement in data processes.

Required Skills and Experience:

• 8 years of experience in data engineering with strong proficiency in Python SQL and datamodeling.
• Expertise in cloud platforms (AWS Azure Google Cloud) including serverless computingand cloud-native services.
• Strong knowledge of data warehousing big data solutions and distributed computing usingPySpark.
• Hands-on experience with machine learning and AI tools with the ability to integratepredictive 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 trackrecord of managing and mentoring technical teams.

Qualifications:

• Bachelors or Masters degree in Computer Science Data Science Information Technologyor related fields.
• Proven experience in managing complex data projects and delivering high-quality scalabledata solutions.
• Strong ability to collaborate with stakeholders and drive strategic data initiatives.

Travel Requirements

Job Posting End Date