IN_Senior Associate_Databricks_Data Analytics_Advisory_Gurugaon at pwc

c, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

27 Mar, 26

Salary

0.0

Posted On

27 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, PySpark, Spark, AWS, Azure, GCP, Data Ingestion, Data Transformation, Data Warehousing, Cloud Services, Problem-Solving, Collaboration, Spark Streaming, Performance Optimization, Communication, Creativity

Industry

Professional Services

Description

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: We are seeking skilled and dynamic Cloud Data Engineers specializing in AWS, Azure, Databricks, and GCP. The ideal candidate will have a strong background in data engineering, with a focus on data ingestion, transformation, and warehousing. They should also possess excellent knowledge of PySpark or Spark, and a proven ability to optimize performance in Spark job executions. Key Responsibilities: - Design, build, and maintain scalable data pipelines for a variety of cloud platforms including AWS, Azure, Databricks, and GCP. - Implement data ingestion and transformation processes to facilitate efficient data warehousing. - Utilize cloud services to enhance data processing capabilities: - AWS: Glue, Athena, Lambda, Redshift, Step Functions, DynamoDB, SNS. - Azure: Data Factory, Synapse Analytics, Functions, Cosmos DB, Event Grid, Logic Apps, Service Bus. - GCP: Dataflow, BigQuery, DataProc, Cloud Functions, Cosmos DB, Event Grid, Logic Apps, Service Bus. - GCP: Dataflow, BigQuery, DataProc, Cloud Functions, Bigtable, Pub/Sub, Data Fusion. - Optimize Spark job performance to ensure high efficiency and reliability. - Stay proactive in learning and implementing new technologies to improve data processing frameworks. - Collaborate with cross-functional teams to deliver robust data solutions. - Work on Spark Streaming for real-time data processing as necessary. Qualifications: - 3-8 years of experience in data engineering with a strong focus on cloud environments. - Proficiency in PySpark or Spark is mandatory. - Proven experience with data ingestion, transformation, and data warehousing. - In-depth knowledge and hands-on experience with cloud services(AWS/Azure/GCP): - Demonstrated ability in performance optimization of Spark jobs. - Strong problem-solving skills and the ability to work independently as well as in a team. - Cloud Certification (AWS, Azure, or GCP) is a plus. - Familiarity with Spark Streaming is a bonus. Mandatory skill sets: Python, Pyspark, SQL with (AWS or Azure or GCP) Preferred skill sets: Python, Pyspark, SQL with (AWS or Azure or GCP) Years of experience required: 3-8 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: Bachelor of Technology, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Engineering, Microsoft Azure 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 January 5, 2026 Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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Responsibilities

The role involves designing, building, and maintaining scalable data pipelines across various cloud platforms. Additionally, the candidate will implement data ingestion and transformation processes to enhance data warehousing efficiency.