IN_Senior Associate_ Data Engineering__ Data & Analytics _ Advisory _Gurgaon

Job Description

Advisory

Not Applicable

Data, Analytics & AI

Senior Associate

Job Description & Summary

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.

• Why PWCAt 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.

We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Certifications: Spark 3.0(Mandatory) and/or Databricks Advanced/Professional Architect.

Additionally, experience with cloud-native data engineering platforms like Databricks, Azure Data Engineering or Amazon Web Services (AWS) is highly desirable.

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.

preferred skill sets:

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

Years of experience required:

Experience: 5 - 8 Years

Education qualification:

B.Tech / M.Tech / MCA/MBA

Degrees/Field of Study required: Master of Engineering, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Databricks Platform, Databricks SQL

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, 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, Embracing Change, Emotional Regulation, Empathy, Geopolitical Forecasting + 24 more

Desired Languages (If blank, desired languages not specified)

Not Specified

No

No

May 29, 2026