INSenior AssociateAzure DatabricksD&AAdvisoryNoida

Why PWC

At PwC 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 about us.

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Role Overview:
Data Engineer with strong hands-on expertise in Azure and Databricks to build
optimize and operate scalable data pipelines and lakehouse solutions. You will partner with architects analysts and business stakeholders to deliver trusted analytics-ready datasets for insurance use cases.

Responsibilities
Design build and support batch and near real-time data pipelines on Azure
using standard engineering practices.
Develop and optimize Databricks notebooks/jobs using PySpark/Spark SQL
and Python; follow code review testing and documentation standards.
Implement and maintain lakehouse tables (Delta) and curated layers; apply
partitioning and file-layout best practices for performance.
Create orchestration and scheduling using Azure Data Factory and/or Databricks Workflows; manage dependencies retries and SLAs.
Implement data quality checks observability (logging/metrics/alerts) and incident triage to ensure reliable pipelines in production.
Apply security and governance controls for regulated/PII data (RBAC encry tion secrets management) and support audits as needed.
Tune Spark workloads and manage Azure/Databricks costs (cluster policies job sizing caching indexing/z-order) to meet performance targets.
Required Skills & Qualifications
Bachelors/masters degree in computer science Engineering or related.
36 years of data engineering experience delivering production pipelines on
Azure.
Strong Databricks expertise (Spark/PySpark) SQL and Python.
Hands-on with Azure data services (ADLS Gen2 ADF) and CI/CD using Git-
based workflows; familiarity with DevOps practices is a plus.
Good understanding of data modeling and lakehouse patterns (Delta).
Strong communication and stakeholder management; ability to translate
requirements into scalable data solutions (insurance domain preferred).
Preferred Attributes
Certifications: Azure Data Engineer Associate and/or Databricks (preferred).
Exposure to Databricks Unity Catalog/Delta Live Tables and insurance data
domains (policy claims billing) is a plus; experience with performance/cost
optimization is valued.