Job Description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

& 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.




In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
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.

& Summary: -

Design and Develop Data Pipelines: Build and optimize scalable ETL processes using PySpark or Scala or SparkSQL to handle large volumes of structured and unstructured data from diverse sources. -Cloud-Based Data Solutions: Implement data ingestion, processing, and storage solutions on the Azure cloud platform, utilizing services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics. -Data Modeling and Management: Develop and maintain data models, schemas, and metadata to ensure efficient data access, high query performance, and support for analytics requirements. -Pipeline Monitoring and Optimization: Monitor the performance of data pipelines, troubleshoot issues, and enhance workflows for scalability, reliability, and cost-efficiency. -Security and Compliance: Enforce data security protocols and compliance measures to safeguard sensitive information and meet regulatory standards.

Responsibilities:

-Experience: Proven track record as a Data Engineer with expertise in building and optimizing data pipelines using PySpark, SQL, and Apache Spark. -Cloud Proficiency: Hands-on experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. -Programming Skills: Strong proficiency in Python ,PySpark, and SQL with experience in software development practices, version control systems, and CI/CD pipelines. -Data Warehousing Knowledge: Familiarity with data warehousing concepts, dimensional modeling, and relational databases such as SQL Server, PostgreSQL, and MySQL. -Big Data Technologies: Exposure to big data frameworks and tools like Hadoop, Hive, and HBase is a plus.

Mandatory skill sets:

-Hands-on experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. -Monitor the performance of data pipelines, troubleshoot issues, and enhance workflows for scalability, reliability, and cost-efficiency.

Preferred skill sets:

Hands-on experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database.

Years of experience required:

4-7 years experience req.

Education qualification:

B.Tech / M.Tech (Computer Science, Mathematics & Scientific Computing etc.)

Education

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

Degrees/Field of Study required: Bachelor of Technology
Degrees/Field of Study preferred:

Certifications

(if blank, certifications not specified)

Required Skills

Microsoft Azure Cloud Services, Microsoft Azure Databricks

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

Desired Languages

(If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date