Job Description

Line of Service Advisory
Industry/Sector Not Applicable
Specialism Data, Analytics & AI
Management Level Manager
& 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 organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational 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.
Responsibilities:
Position: Data Engineering / Manager Experience: 9- 12 Years Location: Bangalore Type: Full Time Certifications: Spark 3.0(Mandatory) and/or Databricks Advanced/Professional Architect. About the Role: We are seeking an experienced and Senior Data Architect with 9-12 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. Key Responsibilities: Design, develop, and maintain scalable data pipelines and architectures using Spark, PySpark, and Python. Lead and manage a team of data engineers, providing technical guidance, mentorship, and performance management. Collaborate with cross-functional teams to understand data requirements and deliver high-quality data solutions. Ensure data quality, integrity, and security across all data engineering projects. Implement best practices for data engineering, including code reviews, testing, and documentation. Stay up-to-date with the latest industry trends and technologies in data engineering and cloud computing. Work closely with stakeholders to understand business needs and translate them into technical requirements. Manage project timelines, resources, and budgets to ensure successful delivery of data engineering projects. Required Skills: 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. Preferred Qualifications: 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.
Mandatory skill sets:
Strong experience with data engineering technologies, particularly Spark, PySpark, and Python.
Additional skill sets preferred:
9+ years of experience in data engineering or related roles. 3+ years of experience in a Technical managerial role. Industry certifications related to data engineering or cloud platforms are a plus.
Years of experience required:
Experience: 9 - 12 Years
Education qualification:
B.Tech / M.Tech / MCA/MBA
Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, Master of Business Administration, Master of Engineering, Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills Data Warehousing Testing, Python (Programming Language), Structured Query Language (SQL)
Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, 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, Data Modeling, Data Pipeline {+ 27 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