Platform Engineer II

Job Summary

Google Cloud Data Engineer:

Key Responsibilities

• Build and Optimize ELT/ETL Pipelines using Big Query, GCS, Dataflow, Pub Sub and Orchestration services Composer/Airflow

• Hands-On experience in building ETL/ELT Pipelines with developing software code in Python

• Experience in working with data warehouses, data warehouse technical architectures, reporting/analytic tools

• Develop and implement data quality and governance procedures to ensure the accuracy and reliability of data

• Demonstrate extensive skills and success in the implementation of technology projects within a professional environment, with a particular focus on data engineering

• Eager to learn and explore new services within GCP to enhance skills and contribution to Projects

• Demonstrated excellent communication, presentation, and problem-solving skills.

• Prior Experience in ETL tool such as DBT,Talend Etc

• Good to have skills

• AI/ML,Gen AI Backgroud

• IAM, Cloud Logging and Monitoring

• The Data Engineer coaches the junior data engineering personnel position by bringing them up to speed and help them get better understanding of overall Data ecosystem.

• Working Experience with Agile methodologies and CI/CD Tools like Terraform/Jenkins

• Working on Solution deck, IP build, client meetings on requirement gathering

Skill Requirements

Technical /

Functional Skills: - • Knowledge in architecture principles, guidelines and standards

• Data Warehousing
• Programming Language: Python, SQL
• Big Data
• Data Analytics
• Experience in Building Streaming and Batch data pipelines with GCP services
  Experience in designing & implementing solution in mentioned areas:
  Cloud Storage, Big Query, Data Flow, Data Proc,
  Pub Sub,Data Fusion,Cloud Function,Composer etc

Other Requirements

Core Competencies (Soft Skills): - Strong communication & presentation- Analytical, client-first mindset- Leadership & stakeholder management- Ability to work in global, fast-paced environment.