Job highlights

- Cloud Certification (AWS,Azure,or GCP) is a plus.
- Preferred skill sets . Python,Pyspark,SQL with (AWS or Azure or GCP) .
- Qualifications . 47 years of experience in data engineering with a strong focus on cloud environments. Proficiency in PySpark or Spark is mandatory.

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 recent technologies to improve data processing frameworks.





Collaborate with crossfunctional teams to deliver robust data solutions.

Work on Spark Streaming for realtime data processing as necessary.

Qualifications

47 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.

Indepth knowledge and handson experience with cloud services(AWS/Azure/GCP)

Demonstrated ability in performance optimization of Spark jobs.

Strong problemsolving 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)

📌 Senior Associate Cloud Data Engineer Data and Analytics Pan India (Bengaluru)
🏢 PwC Acceleration Centers in India
📍 Bengaluru