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 programs, 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.
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.
Responsibilities:
Design and build data pipelines & Data lakes to automate ingestion of structured and unstructured data that provide fast, optimized, and robust end-to-end solutions. Knowledge about the concepts of data lake and data warehouse. Experience working with AWS big data technologies. Improve the data quality and reliability of data pipelines through monitoring, validation, and failure detection. Deploy and configure components to production environments. Technology: Redshift, S3, AWS Glue, Lambda, SQL, PySpark, SQL.
Mandatory skill sets:
AWS Data Engineer
Preferred skill sets:
AWS Data Engineer
Years of experience required:
4-8
Education qualification:
Btech/MBA/MCA
Degrees/Field of Study required: Bachelor of Technology, Bachelor of Engineering. Degrees/Field of Study preferred: