Azure + Databricks - Senior Associate

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you'll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You'll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data and Analytics Engineering team, you will lead the end-to-end implementation of innovative cloud data engineering solutions. As a Senior Associate, you will analyze complex problems, mentor junior team members, and build meaningful client relationships while navigating the intricacies of the data landscape. This role offers the chance to deepen your technical skills and enhance your professional brand in a dynamic and collaborative environment.

Responsibilities:

• Design and develop data solutions using Azure Databricks
• Collaborate with cross-functional teams to deliver analytics projects
• Analyze data to derive actionable insights for clients
• Enhance data processing workflows for efficiency
• Mentor and support junior data engineers in their tasks
• Stay informed on advancements in data engineering technologies
• Maintain adherence to data governance and security protocols
• Conduct training sessions on recommended practices in data management

What You Must Have:

• Bachelor's degree in Engineering, MCA, M.Sc, M.E, M.Tech, MBA
• 4 years of experience
• Oral and written proficiency in English required
• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

What Sets You Apart:

• Certifications in Azure or Databricks
• Excelling in Azure cloud and data engineering solutions
• Demonstrating planning and organization skills
• Leading cloud development on agile teams
• Understanding data management concepts and data modeling
• Skilled in SQL and data extraction techniques
• Utilizing Big Data frameworks like Hadoop and Spark
• Knowledgeable in application DevOps tools and processes