IN_Senior Associate_Azure Databricks_D&A_Advisory_Noida

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 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.

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
• Bachelor’s/master’s degree in computer science, Engineering, or related.
• 3–6 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.