Cloud Data Engineer (AWS/Azure/Databricks/GCP)

1 Month ago • 4-7 Years • Data Analysis

Job Summary

Job Description

As a Cloud Data Engineer at PwC, you will be responsible for designing and building data infrastructure and systems to enable efficient data processing and analysis. This involves developing and implementing data pipelines, data integration, and data transformation solutions across various cloud platforms, including AWS, Azure, Databricks, and GCP. You will also optimize Spark job performance, collaborate with cross-functional teams, and stay updated with new technologies. This role requires you to transform raw data into actionable insights, enabling informed decision-making and driving business growth. You will be working with cross-functional teams to deliver robust data solutions.
Must have:
  • 4-7 years of data engineering experience in cloud environments.
  • Proficiency in PySpark or Spark is mandatory.
  • Experience with data ingestion, transformation and data warehousing.
  • Hands-on experience with AWS/Azure/GCP cloud services.
  • Proven ability in Spark job performance optimization.
  • Strong problem-solving and teamwork skills.
  • Python, Pyspark, SQL with (AWS or Azure or GCP)
Good to have:
  • Cloud Certification (AWS, Azure, or GCP).
  • Familiarity with Spark Streaming is a bonus.
  • Accepting Feedback, Analytical Thinking, Communication, Creativity, Data Engineering, etc.

Job Details

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 PWC 

 

 

Responsibilities: 

Job Title: Cloud Data Engineer (AWS/Azure/Databricks/GCP) 

Experience:4-7 years in Data Engineering 

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, 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: 

- 4-7 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: 

7-10 

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 Engineering, Master of Business Administration, Bachelor of Technology, Master of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

PySpark, 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 {+ 28 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

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About The Company

At PwC, our purpose is to build trust in society and solve important problems. We’re a network of firms in 152 countries with over 327,000 people who are committed to delivering quality in assurance, advisory and tax services. Find out more and tell us what matters to you by visiting us at www.pwc.com. PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity.


Content on this page has been prepared for general information only and is not intended to be relied upon as accounting, tax or professional advice. Please reach out to your advisors for specific advice.

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