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PwC India is seeking a skilled SAP BW4HANA data engineer to design and implement robust data pipelines and modelling solutions. You will work on end-to-end BW4HANA developments, data integration, and performance tuning to support enterprise analytics across client engagements.
The role involves collaboration with architects, analytics teams, and business stakeholders to ensure scalable data models, reliable reporting, and seamless integration with SAP Analytics Cloud and Datasphere.
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.
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 about us.
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.
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.
Experience – 5- 9 Years
Object assessment, Data model redesign using Datasphere best practices, Validation and reconciliation of migrated data.
‘Must have’ knowledge, skills and experiences
‘Good to have’ knowledge, skills and experiences
Reporting tools (SAP Analytics Cloud, Business Objects)
SAP Datasphere & BW4HANA Certification (plus)
Problem-solving & system optimization
Strong communication & client interaction
Project management & business collaboration
5-9 years relevant experience
BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)
Master of Engineering, Bachelor of Engineering
Education (if blank, degree and/or field of study not specified)
Certifications (if blank, certifications not specified)
Full Life Cycle Implementation, SAP Implementations
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, 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 {+ 30 more}