Cloud Data Engineer I, Professional Services, Google Cloud

• Own challenging, non-routine problems end-to-end: identify the underlying need, process complex datasets, and apply advanced data engineering, data modleing, and architectural frameworks when needed.
• Proactively design, build, and scale innovative data products, including self-serve tools, and automated pipelines,.
• Advance data infrastructure, product quality, and foundational understanding through automated validation frameworks, data quality, and reliabilyt monitoring.
• Operate with a high degree of autonomy, owning complex data engineering projects from initial conception to landing and impact
• Advocate impactful data products while contributing to a team culture that values engineering excellence, robust data, and sharp communication.

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
  
• 3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
  
• Experience building and maintaining production data pipelines that rely on multiple upstream data sources.
  
• Experience writing automated tests and validation for data pipelines.
  

Preferred qualifications:

• Experience in technical consulting.
  
• Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
  
• Experience working with Big Data, information retrieval, data mining, or machine learning.
  
• Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
  
• Experience with Server Platform, Compute infrastructure, gcl, Spanner, or Flume.

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
  
• 3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
  
• Experience building and maintaining production data pipelines that rely on multiple upstream data sources.
  
• Experience writing automated tests and validation for data pipelines.