IN Senior Associate Senior Data Engineer Data and Analytics Advisory Bangalore

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & 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.

Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Responsibilities:

About the Role: We are hiring sharp, hands-on Data Engineers to build scalable data solutions and drive performance across both traditional and cloud-based data platforms. If you love writing clean code, solving tough data problems, and designing robust data architectures, this role is for you. What you will do: · Design and implement scalable data pipelines for batch and near real-time use cases in cloud environments · Write optimized, complex SQL queries for data transformation and analysis in cloud data warehouses · Develop efficient Python and PySpark scripts for large-scale data processing and ETL workflows · Create and maintain data models in Databricks, ensuring data quality and consistency · Optimize queries and scripts over large-scale datasets (TBs) with a focus on performance and cost-efficiency · Implement data governance and security best practices in cloud environments · Collaborate across teams to translate business requirements into robust technical solutions

Mandatory skill sets:

‘Must have’ knowledge, skills and experiences · 5+ years of hands-on experience in Data Engineering · Strong command over SQL, Python, and PySpark for data manipulation and analysis · Deep experience with data warehousing concepts and implementation in cloud environments (Azure/GCP) · Proficiency in data modeling techniques for cloud-based systems (Databricks) · Solid understanding of ETL/ELT processes and best practices in cloud architectures · Experience with dimensional modeling, star schemas, and data mart design · Strong analytical thinking and problem-solving skills

Preferred skill sets:

‘Good to have’ knowledge, skills and experiences · Familiarity with data lake architectures and delta lake concepts · Knowledge of data warehouse migration strategies to cloud · Experience with real-time data streaming technologies (e.g., Apache Kafka, Azure Event Hubs)

· Exposure to data quality and data governance tools and methodologies · Understanding of data virtualization and federated query engines · Understanding of performance optimization techniques for cloud-based data warehouses · Certifications in Azure (e.g., Azure Data Engineer) or GCP (e.g., Professional Data Engineer)

Years of experience required:

Experience · 5-10 years

Education qualification:

o BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)

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

Degrees/Field of Study required: Master of Business Administration, Master of Engineering, Bachelor of Technology, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Data Warehousing Testing, Python (Programming Language), Structured Query Language (SQL)

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

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date