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Price Waterhouse Cooper LLP (PwC) is seeking an experienced Senior Associate in Data Engineering to lead engagements and deliver scalable data solutions. You will design pipelines using Spark, PySpark and Python, guide a team of data engineers, and collaborate with stakeholders to transform business needs into robust data architectures.
The role emphasizes cloud-native platforms such as Databricks, AWS, and Azure, data quality and security, and staying ahead with the latest industry trends.
At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.
In business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision-making for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage.
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour 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 foreach 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. "
Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organizations 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 organizations 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.
We are seeking an experienced and Senior Associate with 5-8 years of experience specializing in data services, data architecture, and data platforms to lead our Data engineering engagements. The ideal candidate will have a strong hands-on background in data engineering with specific expertise in Spark, PySpark, and Python. Additionally, experience with cloud-native data engineering platforms like Databricks, Azure Data Engineering or Amazon Web Services (AWS) is highly desirable.
Proven track record of designing and building scalable data pipelines and architectures.
Hands-on experience with data processing and transformation.
Strong understanding of data warehousing concepts and ETL processes.
Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
Strong leadership and team management skills.
Effective communication skills, both written and verbal .
Experience with cloud-native data engineering on platforms such as Databricks and Azure/AWS.
Familiarity with cloud services related to data storage, processing, and analytics (e.g., BigQuery, Redshift, S3, EMR).
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
Experience with data visualization tools and techniques.
Familiarity with machine learning and data science concepts.
Experience: 5 - 8 Years
Degrees/Field of Study required: Bachelor of Engineering
PySpark
Accepting Feedback, Accepting Feedback, Active Listening, AI Fluency, AI-Human Collaboration, Analytical Thinking, Applied Macroeconomics, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Digital Tooling, Embracing Change {+ 27 more}