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Lead Data Engineer with Google Cloud Platform, Python
Salary undisclosed
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Position: Lead Data Engineer
Location: 100% Remote (EST time zone)
Contract Duration: 12+ years
Summary:
- Need candidates that can confidently build and maintain the data infrastructure that supports the data-related initiatives.
- This person will need hands on Python experience and the heavy data background.
- Focus will be developing scalable data pipelines, optimizing data workflows, and ensures the quality of the data.
- Anyone with a Google Professional Data Engineer Certification will be interviewed first
Qualifications:
- 10+ years of Overall IT experience with at least 5+ years working in Data Engineering.
- Previous Healthcare experience
- Must have Google Cloud Platform experience
- Google Professional Data Engineer Certification
- 5+ years of experience with SQL, NoSQL
- 5+ years of experience with Python
- 5+ years of experience with Data warehouses and infrastructure components
- 5+ years of experience with ETL/ELT and building high-volume data pipelines.
- 5+ years of experience with reporting/analytic tools
- 5+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management
- 5+ years of experience with Big Data and cloud architecture
- 5+ years of hands-on experience building modern data pipelines within a major cloud platform - Ideally Google Cloud Platform
- 5+ years of experience with real-time and streaming technology
- 3-5 years of experience with deployment/scaling of apps on containerized environment
Nice to Haves:
- Experience in designing and building data engineering solutions in cloud environments (preferably Google Cloud Platform)
- Experience with Git, CI/CD pipeline, and other DevOps principles/best practices
- Experience with bash shell scripts, UNIX utilities & UNIX Commands
- Knowledge of API development
- Experience with complex systems and solving challenging analytical problems.
- Strong collaboration and communication skills within and across teams
- Knowledge of data visualization and reporting
- Experience with schema design and dimensional data modeling
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job Position: Lead Data Engineer
Location: 100% Remote (EST time zone)
Contract Duration: 12+ years
Summary:
- Need candidates that can confidently build and maintain the data infrastructure that supports the data-related initiatives.
- This person will need hands on Python experience and the heavy data background.
- Focus will be developing scalable data pipelines, optimizing data workflows, and ensures the quality of the data.
- Anyone with a Google Professional Data Engineer Certification will be interviewed first
Qualifications:
- 10+ years of Overall IT experience with at least 5+ years working in Data Engineering.
- Previous Healthcare experience
- Must have Google Cloud Platform experience
- Google Professional Data Engineer Certification
- 5+ years of experience with SQL, NoSQL
- 5+ years of experience with Python
- 5+ years of experience with Data warehouses and infrastructure components
- 5+ years of experience with ETL/ELT and building high-volume data pipelines.
- 5+ years of experience with reporting/analytic tools
- 5+ years of experience with Query optimization, data structures, transformation, metadata, dependency, and workload management
- 5+ years of experience with Big Data and cloud architecture
- 5+ years of hands-on experience building modern data pipelines within a major cloud platform - Ideally Google Cloud Platform
- 5+ years of experience with real-time and streaming technology
- 3-5 years of experience with deployment/scaling of apps on containerized environment
Nice to Haves:
- Experience in designing and building data engineering solutions in cloud environments (preferably Google Cloud Platform)
- Experience with Git, CI/CD pipeline, and other DevOps principles/best practices
- Experience with bash shell scripts, UNIX utilities & UNIX Commands
- Knowledge of API development
- Experience with complex systems and solving challenging analytical problems.
- Strong collaboration and communication skills within and across teams
- Knowledge of data visualization and reporting
- Experience with schema design and dimensional data modeling
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job