Job Title: Google Data Engineer / Lead
Experience: 5-15 years

Job Summary: An experienced Google Data Engineer / Lead to design, develop, and maintain large-scale data processing systems on Google Cloud Platform (GCP). The ideal candidate should have a robust background in data engineering, data warehousing, and cloud-based data platforms.

Responsibilities:
Data Pipeline Development: Design, develop, and maintain data pipelines using Google Cloud Dataflow, Cloud Composer, and BigQuery.
Data Warehousing: Work with data architects and business stakeholders to design and implement data warehousing solutions using BigQuery and Cloud Storage.
Data Governance: Develop and maintain data governance policies, procedures, and standards for GCP.
Collaboration: Work with cross-functional teams to identify and prioritize project requirements, provide technical guidance, and ensure data quality.
Cost Optimization: Optimize GCP costs and ensure data processing efficiency.

Required Skills:
Google Cloud Platform: In-depth knowledge of GCP, including Cloud Dataflow, BigQuery, Cloud Storage,



and Cloud Composer.
Data Engineering: Strong understanding of data engineering concepts, including data modeling, ETL, and data warehousing.
Expertise in Cloud storage, Dataproc, Cloud Functions, Messaging/Streaming (pub-sub)
Programming: Proficiency in programming languages, including Python, Java, or SQL.
Data Governance: Familiarity with data governance frameworks, including data quality, data security, and data compliance.
Communication: Excellent communication and collaboration skills.

Preferred Skills:
Google Cloud Certifications: Relevant certifications, such as Google Cloud Certified - Professional Data Engineer or Google Cloud Certified - Enterprise Data Engineer.
Big Data: Experience with big data technologies, including Hadoop, Spark, or NoSQL databases.
Machine Learning: Experience with machine learning frameworks, including TensorFlow or Scikit-learn.
Cloud Experience*: Experience

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