📍 Job Overview

Job Title: Cloud Data Platform - PL/SQL Developer Senior Associate [ADV]
Company: PwC
Location: Milan, Lombardy, Italy
Job Type: Full-Time
Category: Data Engineering
Date Posted: 2025-05-22
Experience Level: 5-10 years
Remote Status: On-site

🚀 Role Summary

Role Focus: Design and implementation of advanced data platforms using innovative architectural patterns.
Industry Exposure: Automotive & Industrial Manufacturing, Consumer Markets, Energy & Utilities, Financial Services, Telco & Media.
Technical Skills: PL/SQL, TSQL, Python, Informatica Power Center, Integration Services, Oracle, SQL Server.
Innovation Focus: Data Mesh, cloud platforms (GCP, AWS, Azure).

📝 Enhancement Note: This role requires a strong background in data engineering and familiarity with cloud platforms to drive innovative data solutions.

💻 Primary Responsibilities

Requirements Gathering & Design: Collaborate with clients to understand their data needs and design appropriate solutions.
Technology Selection: Evaluate and recommend suitable technologies for various project contexts.
Data Processing: Implement data collection, transformation, and modeling processes using tools like Informatica Power Center, Oracle, and SQL Server.
Architectural Innovation: Study and implement cutting-edge architectural patterns, such as Data Mesh.
Project Management: Oversee data projects from inception to completion, ensuring quality and timely delivery.

📝 Enhancement Note: This role requires a balance of technical depth and project management skills to successfully deliver complex data projects.

🎓 Skills & Qualifications

Education: A degree in Computer Science, Engineering, Mathematics, or Physics is required. Relevant certifications in Informatica, Oracle, or MS SQL Server are preferred.

Experience: 5-10 years of experience in data engineering, with a strong focus on data processing, transformation, and modeling. Proven experience in cloud platforms is a plus.

Required Skills:

Proficiency in PL/SQL, TSQL, and Python.
Strong knowledge of Informatica Power Center and Integration Services.
Experience with Oracle or SQL Server database management.
Understanding of data infrastructure, architecture, and trends.
Excellent communication and analytical thinking skills.

Preferred Skills:

Familiarity with cloud platforms (GCP, AWS, Azure).
Experience with data warehousing frameworks and lifecycle.
Knowledge of data quality, integrity, and security principles.
Ability to embrace change and adapt to new technologies.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate proficiency in data processing, transformation, and modeling through relevant projects.
Showcase experience with Informatica Power Center, Oracle, and SQL Server.
Highlight any exposure to cloud platforms and innovative architectural patterns.

Technical Documentation:

Include detailed project documentation, highlighting data processing workflows, transformation rules, and data models.
Showcase any experience with data quality, integrity, and security measures.
Demonstrate understanding of data warehousing trends and best practices.

📝 Enhancement Note: A strong portfolio will showcase the candidate's ability to design, implement, and manage complex data projects, with a focus on data quality, security, and innovation.

💵 Compensation & Benefits

Salary Range: €60,000 - €80,000 per year (based on experience and market research).

Benefits:

Competitive salary and benefits package.
Opportunities for professional development and growth.
Collaborative and innovative work environment.

Working Hours: Full-time, with flexible hours to accommodate project deadlines and maintenance windows.

📝 Enhancement Note: The salary range is based on market research for data engineering roles in Milan, Italy, and may vary depending on experience and negotiation.

🎯 Team & Company Context

🏢 Company Culture

Industry: PwC operates in the professional services industry, focusing on advisory, tax, and assurance services for a wide range of clients.

Company Size: PwC is a multinational professional services network with over 276,000 employees worldwide, providing ample opportunities for collaboration and growth.

Founded: PwC was founded in 1849, with a rich history in professional services and a strong commitment to innovation and client success.

Team Structure:

The Cloud Engineering team focuses on driving digital transformation through advanced data platforms and cloud technologies.
The team consists of professionals with diverse backgrounds in data engineering, cloud architecture, and project management.
Collaboration is key, with cross-functional teams working together to deliver innovative solutions for clients.

Development Methodology:

PwC follows Agile methodologies for project management, with a focus on iterative development and continuous improvement.
Code reviews, testing, and quality assurance practices are integral to the development process.
Deployment strategies, CI/CD pipelines, and server management are essential for delivering high-quality solutions.

Company Website: https://www.pwc.com/gx/en.html

📝 Enhancement Note: PwC's size and global presence offer numerous opportunities for collaboration, growth, and exposure to diverse industries and technologies.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior associate level, requiring a strong technical background in data engineering and proven experience in managing complex data projects.

Reporting Structure: The role reports to the Cloud Engineering team lead, with opportunities for collaboration and mentorship from senior team members.

Technical Impact: The role has a significant impact on data projects, driving innovation through the implementation of advanced data platforms and architectural patterns.

Growth Opportunities:

Technical Growth: Deepen expertise in data engineering, cloud platforms, and emerging technologies.
Leadership Growth: Develop project management and team leadership skills through managing complex data projects.
Career Progression: Advance to manager or principal consultant roles, focusing on strategic client relationships and team leadership.

📝 Enhancement Note: This role offers significant growth opportunities, with a focus on technical expertise, project management, and leadership development.

🌐 Work Environment

Office Type: PwC's Milan office is a modern, collaborative workspace designed to foster innovation and teamwork.

Office Location(s): Milan, Italy.

Workspace Context:

Collaborative Environment: The office features open-plan workspaces, encouraging collaboration and knowledge sharing.
Development Tools: The office is equipped with state-of-the-art development tools, multiple monitors, and testing devices.
Cross-Functional Collaboration: The office is home to various teams, promoting cross-functional collaboration between data engineers, designers, and stakeholders.

Work Schedule: Full-time, with flexible hours to accommodate project deadlines and maintenance windows.

📝 Enhancement Note: PwC's Milan office provides a collaborative and innovative work environment, with ample opportunities for cross-functional collaboration and professional growth.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: A technical assessment focused on data processing, transformation, and modeling using PL/SQL, TSQL, Python, and relevant tools.
Architectural Discussion: A discussion on architectural patterns, such as Data Mesh, and their application to real-world projects.
Behavioral Interview: An interview focused on problem-solving, communication, and teamwork skills.
Final Evaluation: A final evaluation based on technical competency, cultural fit, and alignment with PwC's values.

Portfolio Review Tips:

Highlight projects that demonstrate proficiency in data processing, transformation, and modeling.
Showcase experience with cloud platforms and innovative architectural patterns.
Include detailed project documentation, highlighting data processing workflows, transformation rules, and data models.

Technical Challenge Preparation:

Brush up on PL/SQL, TSQL, Python, and relevant tools.
Familiarize yourself with data warehousing trends and best practices.
Prepare for discussions on cloud platforms and architectural patterns.

ATS Keywords: PL/SQL, TSQL, Python, Informatica Power Center, Integration Services, Oracle, SQL Server, Data Engineering, Data Processing, Data Transformation, Data Modeling, Data Quality, Data Security, Data Warehousing, Cloud Platforms, GCP, AWS, Azure, Agile, Project Management, Teamwork.

📝 Enhancement Note: The interview process focuses on technical competency, problem-solving, and cultural fit, with a strong emphasis on data engineering skills and cloud platform experience.

🛠 Technology Stack & Web Infrastructure

Data Processing & Transformation:

PL/SQL
TSQL
Python
Informatica Power Center
Integration Services

Database Management:

Oracle
SQL Server

Cloud Platforms:

GCP
AWS
Azure

Project Management & Collaboration:

Agile methodologies
JIRA
Confluence

📝 Enhancement Note: The technology stack focuses on data processing, transformation, and modeling, with a strong emphasis on cloud platforms and Agile methodologies.

👥 Team Culture & Values

Data Engineering Values:

Innovation: Pursue cutting-edge technologies and architectural patterns to drive data project success.
Quality: Ensure data accuracy, integrity, and security through robust data processing and transformation workflows.
Collaboration: Work closely with cross-functional teams to deliver high-quality data solutions that meet client needs.
Continuous Learning: Stay up-to-date with emerging technologies and best practices in data engineering.

Collaboration Style:

Cross-Functional Integration: Collaborate with designers, marketers, and other stakeholders to ensure data solutions meet user needs.
Code Review Culture: Foster a culture of code review and peer programming to maintain high-quality data processing and transformation workflows.
Knowledge Sharing: Encourage knowledge sharing and technical mentoring to drive continuous learning and improvement.

📝 Enhancement Note: PwC's data engineering team values innovation, quality, collaboration, and continuous learning, with a strong emphasis on cross-functional collaboration and knowledge sharing.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Complexity: Design and implement data processing and transformation workflows for complex, high-volume datasets.
Architectural Innovation: Stay up-to-date with emerging architectural patterns, such as Data Mesh, and apply them to real-world projects.
Cloud Migration: Migrate on-premises data platforms to cloud-based solutions, optimizing for scalability, performance, and cost-efficiency.
Data Governance: Ensure data quality, integrity, and security through robust data processing and transformation workflows.

Learning & Development Opportunities:

Technical Skills: Deepen expertise in data engineering, cloud platforms, and emerging technologies through training, workshops, and online resources.
Leadership Skills: Develop project management and team leadership skills through managing complex data projects and mentoring junior team members.
Industry Exposure: Gain exposure to diverse industries and clients, driving innovative data solutions that meet unique business needs.

📝 Enhancement Note: This role presents significant technical challenges and growth opportunities, with a focus on data complexity, architectural innovation, cloud migration, and data governance.

💡 Interview Preparation

Technical Questions:

Data Processing & Transformation: Prepare for questions on PL/SQL, TSQL, Python, and relevant tools, with a focus on data processing, transformation, and modeling workflows.
Architectural Patterns: Brush up on emerging architectural patterns, such as Data Mesh, and prepare for discussions on their application to real-world projects.
Cloud Platforms: Familiarize yourself with GCP, AWS, and Azure, and prepare for discussions on cloud migration, scalability, performance, and cost-efficiency.

Company & Culture Questions:

PwC Values: Research PwC's core values and be prepared to discuss how you embody them in your work.
Client Focus: Prepare for questions on how you prioritize client needs and deliver high-quality data solutions that meet their unique business requirements.
Teamwork: Be ready to discuss your experience working in cross-functional teams and driving collaborative data solutions.

Portfolio Presentation Strategy:

Project Selection: Choose projects that showcase your proficiency in data processing, transformation, and modeling, with a focus on cloud platforms and architectural innovation.
Storytelling: Prepare engaging narratives that highlight the challenges, solutions, and outcomes of your data projects.
Technical Deep Dive: Be ready to dive deep into the technical aspects of your projects, highlighting your expertise in data engineering and cloud platforms.

📝 Enhancement Note: The interview process focuses on technical competency, problem-solving, and cultural fit, with a strong emphasis on data engineering skills and cloud platform experience.

📌 Application Steps

To apply for this Cloud Data Platform - PL/SQL Developer Senior Associate [ADV] position at PwC:

Customize Your Portfolio: Highlight projects that demonstrate your proficiency in data processing, transformation, and modeling, with a focus on cloud platforms and architectural innovation.
Optimize Your Resume: Emphasize your technical skills in data engineering, cloud platforms, and project management, with a focus on relevant keywords and project highlights.
Prepare for Technical Interviews: Brush up on PL/SQL, TSQL, Python, and relevant tools, and familiarize yourself with data warehousing trends and best practices.
Research PwC: Learn about PwC's core values, industry focus, and commitment to innovation and client success.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with PwC before making application decisions.

Cloud Data Platform - PL/SQL Developer Senior Associate [ADV]