Associate Data Analytics Engineer

Round 1: Technical coding (Python/SQL) → Round 2: Technical interview (Data Engineering concepts) → Round 3: HR interview

PwC fosters an inclusive culture that values collaboration, continuous learning, and work‑life balance. Employees enjoy ample growth opportunities, mentorship programs, and a supportive environment that encourages innovation and professional development.

Candidates typically go through a three‑round interview process: a technical coding test focused on Python/SQL, a technical interview covering data engineering concepts and problem‑solving, and an HR interview to assess cultural fit. The difficulty is moderate to high, with emphasis on real‑world scenarios and practical knowledge. Preparation tips include practicing coding challenges, reviewing data pipeline design, and staying updated on Azure and Databricks features.

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. 1–3 years of relevant experience in data engineering or software development. Minimum 60% marks in the final year or equivalent. No backlogs allowed. Candidates should be recent graduates or within 3 years of graduation.

PwC Acceleration Center India is a global hub that brings together world‑class advisory, assurance, tax and business services to deliver innovative solutions for clients across multiple geographies. The center focuses on digital transformation, leveraging advanced analytics, cloud technologies and AI to help clients stay ahead in a rapidly changing business environment. With a culture of collaboration, continuous learning and a commitment to diversity, PwC offers a platform where fresh talent can grow into industry leaders. The Data Engineer – Associate role is designed for recent graduates or early‑career professionals who are passionate about building scalable data solutions. As an associate, you will work closely with senior engineers and client teams to design, develop and maintain data pipelines that power analytics and decision‑making. Your responsibilities will include coding in Python and SQL, orchestrating Spark jobs on Databricks, and deploying cloud‑based data lakes and warehouses on Azure. You will also contribute to emerging GenAI initiatives, applying retrieval‑augmented generation techniques to enhance data products. Key responsibilities: 1. Design and develop end‑to‑end data pipelines using Python, Spark and Databricks. 2. Build and maintain Azure‑based data lakes, lakehouses and data warehouses. 3. Implement Delta Lake and Delta Live Tables for reliable data ingestion. 4. Collaborate with stakeholders to translate business requirements into technical specifications. 5. Perform data modeling, schema design and performance tuning. 6. Write unit tests, conduct debugging and troubleshoot production issues. 7. Use Git, CI/CD pipelines and best practices for code quality. 8. Participate in GenAI and RAG projects under guidance. 9. Continuously learn new tools and improve engineering practices. 10. Mentor junior team members and share knowledge. Tech stack: Python, SQL, Spark, Databricks, Azure Data Factory, Azure Synapse, Delta Lake, Lakehouse, Git, CI/CD. Growth path: Starting as an associate, you can progress to Senior Data Engineer, Lead Engineer, and eventually move into technical leadership or consulting roles within PwC’s global network. Why join PwC? The firm offers competitive compensation, a supportive learning environment, exposure to high‑impact projects, and a global career trajectory. Employees benefit from mentorship, structured training, and the opportunity to work with cutting‑edge technologies while contributing to meaningful business outcomes. Overall, this role is ideal for data enthusiasts who want to build a solid foundation in data engineering, work on real‑world challenges, and grow within a respected global organization.