IN_Manager__Databricks Data Engineer_GCC_Advisory_Gurgaon

PwC India; Gurugram District; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Price Waterhouse Cooper LLP is seeking an experienced Data Engineer - Databricks in India to design, build, and operate scalable data pipelines on the Databricks Lakehouse platform. You will work with Spark, PySpark, Delta Lake, and cloud services to enable analytics and AI/ML workloads.

The role requires 6+ years of data engineering experience, strong Databricks skills, and expertise in SQL, ETL/ELT, and governance.

Qualifications

• 6+ years of experience as a Data Engineer.
• Strong Databricks expertise; hands-on with Spark, PySpark, Spark SQL.
• Deep knowledge of Delta Lake and Lakehouse architecture.
• Advanced SQL skills; experience with ETL/ELT patterns.
• Exposure to at least one cloud platform (Azure / AWS / GCP).
• Experience working in Agile teams.

Responsibilities

• Design and maintain end-to-end data pipelines on Databricks (PySpark / Spark SQL).
• Implement batch and incremental processing with Delta Lake.
• Develop and optimize Databricks notebooks, jobs, and workflows.
• Ingest, transform, and curate large-scale datasets.
• Collaborate with data scientists, analysts, and architects on AI/ML workloads.
• Provide production support and troubleshoot data pipelines.

Skills

Generative AI

Databricks

Spark / PySpark

Spark SQL

Delta Lake

Lakehouse architecture

Cloud platforms

Agile

SQL

Education

Bachelor of Engineering

Master of Engineering

Bachelors/Masters in CS or Engineering

Tools

Databricks

Apache Spark

PySpark

Spark SQL

Delta Lake

Azure / AWS / GCP

Job description

Job Description & 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.

Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation.

WhyPWC

AtPwC, 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

AtPwC, 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

We are seeking an experienced Data Engineer - Databricks to design, build, and operate scalable, high-performance data pipelines on the Databricks Lakehouse Platform. The role involves hands-on development using Apache Spark, Databricks notebooks, Delta Lake, and cloud-native services, along with close collaboration with analytics, AI/ML, and business teams

Responsibilities

• Design, build, and maintain end-to-end data pipelines using Databricks (PySpark / Spark SQL)
• Implement batch and incremental data processing using Delta Lake and multi-hop architecture
• Develop and optimize Databricks notebooks, jobs, and workflows
• Ingest, transform, and curate large-scale structured and semi-structured datasets
• Support analytics, reporting, and downstream data consumption use cases
• Ensure data quality, reliability, lineage, and governance
• Collaborate with data scientists, analysts, and architects on AI/ML workloads
• Optimize Spark jobs for performance and cost efficiency
• Adhere to enterprise security, access control, and compliance standards
• Provide production support and troubleshoot data pipeline issues
• Document technical designs, data flows, and operational runbooks
• Mentor junior engineers and contribute to best practices

Mandatory skill sets

• 6+ years of experience as a Data Engineer with strong Databricks expertise
• Hands-on experience with Apache Spark, PySpark, and Spark SQL
• Strong knowledge of Delta Lake and Lakehouse architecture
• Advanced SQL skills
• Experience with ETL/ELT patterns and data warehousing concepts
• Exposure to at least one cloud platform (Azure / AWS / GCP)
• Understanding of distributed computing concepts
• Experience working in Agile teams

Preferred skill sets

• Experience with Unity Catalog and data governance
• Exposure to Auto Loader or streaming frameworks
• CI/CD for data pipelines
• Python for data engineering and automation

Years of experience required

6-10 years

Education

(if blank, degree and/or field of study not specified)

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

Degrees/Field of Study preferred:

Bachelor's or Master's degree in Computer Science, Engineering, or related field (60% above)

Certifications

(if blank, certifications not specified)

Required Skills

Generative AI

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, AI Fluency, AI-Human Collaboration, AI Implementation, Analytical Thinking, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Digital Tooling, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion {+ 33 more}

Desired Languages

(If blank, desired languages not specified)