Senior Associate, Data Engineering

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.

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:

• We are seeking an experienced 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.
• 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.

Preferred skill sets:

• Proven experience in data engineering or related roles.
• Industry certifications related to data engineering or cloud platforms are a plus.

Education qualification:

B.Tech / M.Tech / MCA / MBA