ZestAmigo
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182 open roles · AI & Data Engineering

Senior Data Specialist - R01569531

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Senior
Posted 1 month ago
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Where you can work

Hybrid

2 workplaces

  • Pune, Maharashtra, India
  • Bengaluru, Karnataka, India
View location wording from the posting
  • Pune, Maharashtra, India
  • Bangalore

Role overview

Extracted from the posting. Read the employer’s full description below.

  • Design and develop scalable ETL/ELT data pipelines on GCP.
  • Implement batch and real-time data processing pipelines.
  • Support cloud migration and modernization initiatives.

What they are looking for

  • Build and optimize data solutions using BigQuery, Dataflow, Dataproc, Cloud Storage, and Pub/Sub .
  • Develop data processing applications using Python, PySpark, and SQL .
  • Perform data ingestion, transformation, cleansing, and validation.
  • Design efficient data models and data warehouse solutions in BigQuery.
  • Optimize pipeline performance and BigQuery queries for scalability and cost efficiency.
Show all 8 items
  • Integrate data from multiple sources into cloud-based data platforms.
  • Implement data quality, security, monitoring, and governance practices.
  • Work closely with Data Scientists, Architects, Analysts, and business stakeholders.

Employer description

GCP Data Engineer-

Location : Bangalore

Experience : +6yrs

About the Role

We are looking for an experienced GCP Data Engineer to design, develop, and optimize scalable data pipelines and cloud-based data solutions on Google Cloud Platform.

The ideal candidate should have strong hands-on experience in GCP Data Engineering, BigQuery, Dataflow, Dataproc, Python/PySpark, and SQL, along with good knowledge of data warehousing and ETL processes.

Primary Skills

🔑 Key Responsibilities

  • Design and develop scalable ETL/ELT data pipelines on GCP.
  • Build and optimize data solutions using BigQuery, Dataflow, Dataproc, Cloud Storage, and Pub/Sub.
  • Develop data processing applications using Python, PySpark, and SQL.
  • Perform data ingestion, transformation, cleansing, and validation.
  • Design efficient data models and data warehouse solutions in BigQuery.
  • Implement batch and real-time data processing pipelines.
  • Optimize pipeline performance and BigQuery queries for scalability and cost efficiency.
  • Integrate data from multiple sources into cloud-based data platforms.
  • Implement data quality, security, monitoring, and governance practices.
  • Work closely with Data Scientists, Architects, Analysts, and business stakeholders.
  • Support cloud migration and modernization initiatives.

Specialization

  • Azure Data Engineering Advanced: Senior Data Engineer
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