GCP Data Engineer

GCP Data Engineer

Key Responsibilities

• Data Pipeline Development

  : Design, build, and maintain robust and scalable data pipelines on the Google Cloud Platform (GCP).

• SQL and PySpark Expertise

  : Utilize very strong expertise in

  SQL

  for data manipulation and querying, and

  PySpark

  for large-scale data processing and transformation.

• GCP Data Services Implementation

  : Work extensively with GCP data services including

  BigQuery

  for data warehousing,

  Dataform

  for data pipeline orchestration and governance, and

  Dataplex

  for data lake management and data governance.

• Data Modeling & Optimization

  : Implement efficient data models and optimize data workflows for performance and cost-effectiveness within the GCP ecosystem.

• Troubleshooting & Performance Tuning

  : Identify and resolve complex data-related issues, performing performance tuning on existing data processes.

• Collaboration

  : Work closely with data scientists, analysts, and other engineering teams to understand data requirements and deliver integrated solutions.

Skills

• Very strong

  hands-on experience as a GCP Data Engineer

  .
• Exceptional proficiency in

  SQL

  for complex data querying and manipulation.
• Very strong experience with

  PySpark

  for distributed data processing.
• Solid experience with

  BigQuery, Dataform, Dataplex

  , and other relevant GCP data services.
• Knowledge of data warehousing concepts and ETL/ELT processes.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
• Proven experience as a Data Engineer with a significant focus on GCP.

• Immediate joiners to currently serving candidates

  are highly preferred.