Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob 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.
*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:
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:
4-7 years
Education qualification:
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, Bachelor of TechnologyDegrees/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 Hadoop, Azure Data Factory, Communication, Creativity, 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 {+ 19 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date