Job Description

Line of Service Advisory
Industry/Sector Not Applicable
Specialism Data, Analytics & AI
Management Level Associate
& Summary 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.
Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more .
At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm's growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.
& Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
Responsibilities:
Design, develop, and maintain robust data pipelines using AWS services such as Glue, Lambda, Redshift, and S3. Implement ETL/ELT processes using PySpark and Airflow to ingest, transform, and load data from various sources including IoT devices and energy systems. Collaborate with cross-functional teams to integrate data from power distribution, control systems, and monitoring platforms. Ensure data quality, integrity, and security across all data platforms. Optimize data workflows for performance, scalability, and cost-efficiency. Support real-time and batch data processing for analytics and reporting on energy usage, system health, and predictive maintenance. Maintain documentation for data architecture, processes, and best practices.
Mandatory skill sets:
3+ years of experience in data engineering with a strong focus on AWS technologies. Proficiency in Python, SQL, PySpark, and data modeling. Hands-on experience with AWS services such as Glue, Re
Preferred skill sets:
Azure, Google Cloud
Years of experience required:
4-8 Years
Education qualification:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor Degree, Master Degree
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills DevOps Engineering
Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Strategy {+ 22 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements Not Specified
Available for Work Visa Sponsorship? No
Government Clearance Required? No
Job Posting End Date

Skills Required