IN_Associate_Data Engineer_Data and Analytics_Advisory_Pan India

Line of Service:

Industry/Sector:

Specialism:

Management Level:

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.

Responsibilities:

• Architecting and designing complex data systems and pipelines.
• Leading and mentoring junior data engineers and team members.
• Collaborating with cross-functional teams to define data requirements.
• Implementing advanced data quality checks and ensuring data integrity.
• Optimizing data processes for efficiency and scalability.
• Overseeing data security and compliance measures.
• Evaluating and recommending new technologies to enhance data infrastructure.
• Providing technical expertise and guidance for critical data projects.

Required Skills & Experience:

• Proficiency in designing and building complex data pipelines and data processing systems.
• Leadership and mentorship capabilities to guide junior data engineers and foster skill development.
• Strong expertise in data modeling and database design for optimal performance.
• Skill in optimizing data processes and infrastructure for efficiency, scalability, and cost-effectiveness.
• Knowledge of data governance principles, ensuring data quality, security, and compliance.
• Familiarity with big data technologies like Hadoop, Spark, or NoSQL.
• Expertise in implementing robust data security measures and access controls.
• Effective communication and collaboration skills for cross-functional teamwork and defining data requirements.

Skills:

• Cloud:

  Azure/GCP/AWS

• DE Technologies:

  ADF, Big Query, AWS Glue

• Data Lake:

  Snowflake, Data Bricks

Mandatory Skill Sets:

• Cloud: Azure/GCP/AWS
• DE Technologies: ADF, Big Query, AWS Glue
• Data Lake: Snowflake, Data Bricks

Preferred Skill Sets:

• Cloud: Azure/GCP/AWS
• DE Technologies: ADF, Big Query, AWS Glue
• Data Lake: Snowflake, Data Bricks

Years of Experience Required:

• 2-4 years

Education Qualification:

• BE/BTECH, ME/MTECH, MBA, MCA

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

• Degrees/Field Of Study Required:

• Master of Engineering, Master of Business Administration, Bachelor of Engineering

• Degrees/Field Of Study Preferred:

• Certifications not specified

Required Skills:

• AWS Glue, Microsoft Azure

Optional Skills:

• Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Hadoop, Azure Data Factory, Communication, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation, Data Validation, Data Warehouse, Data Warehouse Indexing, and more.

Desired Languages (if blank, desired languages not specified):

• Not specified

Travel Requirements:

• Not Specified

Available for Work Visa Sponsorship

• No

Government Clearance Required

• No