Google Cloud Data Engineer
Jobgether (company site, opens in a new tab)3–10 yrsRemoteDirect career pageEst. 12–30 LPA
Posted 1d ago
Reach people at Jobgether
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Jobgether you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain scalable end-to-end data platforms and pipelines on Google Cloud tailored to business requirements, including for clients in regulated industries.
- Ensure data quality, governance, security, and compliance with data residency requirements while optimizing performance and cost-efficiency of data solutions.
- Take full ownership of data engineering delivery lifecycle, including architecture decisions, implementation, deployment, monitoring, and continuous optimization.
Minimum Requirements
- 3 to 10 years of hands-on data engineering experience, specifically designing and maintaining solutions on Google Cloud Platform (GCP).
- Strong proficiency in complex SQL and advanced Python for data pipeline development and processing logic implementation.
- Experience designing reliable data pipelines that handle late-arriving, duplicate, and inconsistent data as well as familiarity with data modeling and governance.
- Availability to overlap approx. 6 hours with North American Eastern Time for client and team collaboration.
Ideal Candidate Profile
- Experienced in large-scale, regulated or enterprise data environments demonstrating strong technical depth over tenure length.
- Capable of independently owning end-to-end data platform solutions from design through production support in a distributed team setting.
- Skilled at balancing scalability, data quality, security, and cost in cloud-based data architectures while communicating effectively with technical and non-technical stakeholders.