GCP CloudOps Engineer
3 weeks ago
W2 Candidates Only Please.......we can not use C2C for this position
Very Long Term Contract position (starts as 12+ months, but will most likely be a few years in duration
Rate: $90-95/hr. W2 with benefits/PTO
GCP CloudOps Engineer (with Data intensive environment experience)
Team:
- Focus is mainly on building data pipelines and solutions for environmental data sets
- Will be only person in this role on the team (other data engineers and data stewards on the sub team). There are other people in this role/peers in other teams doing the same role they will be able to speak with. But expectations is to complete the needs independently for this team.
Role:
- Mainly work on deploying and maintain cloud infrastructures.
- Adding observabilities to their pipelines & services
- ID opportunities for workflow optimization & cloud cost effectiveness/savings.
- Implementing the CI/CD pipelines for their data pipelines
- Cloud: GCP preferred, will be expanding footprint in GCP for a bunch of projects.
- GCP is their preference. AWS acceptable. If you have two equal profiles in all the skills, they will select GCP proficiency over AWS.
- Experience with mutli cloud preferable (GCP/AWS preferred)
- IaC - Terraform
- Programming – Golang and/or Python – used for automation.
- Golang preferred (working on a lot of google resources; native lang. to be able to write automation for a bunch of stuff they are working on)
- Python also preferred.
- Bash – write command lines, etc
- Containerization: apps deployed in Docker, and Kubernetes (orchestration)
- Not a software dev but need to be able to develop automation or implement automation.
- Monitoring and adding observability to their services is critical function – proficiency in tool needed. Grafana, Prometheus, etc.
- Build the baseline then identify the SLI, and build things SLO, SLA’ to commit to customer.
- Security principles – building secure and compliant solution.
DATA Background:
- Extensive cloud infrastructure mgmt. in a data intensive environment (bc they are data engineering team.)
THIS MEANS:
- Work experience handling terabytes or petabytes of the data; magnitude of data. The solution will be different in terms of processing big data as opposed to dealing with mega or gigabytes of data.
- 2Modern data processing technologies or data pipelines or workflows involved. Meaning: data coming from various different sources such as data collected by IoT, and there are things like data streaming, data ingestion, data pipelining involved.
SCALE MATTERS & PERFORMANCE MATTERS ^ there are different solutions for huge data and working with modern data processing technologies.
- Background in data environment & familiar w Data Engineering concepts.
- A lot of data products in CS Warehouse built on top of Google Big Query
- A lot of the data pipelines or services will have the input/output connection with data warehouse so that’s where a basic understanding of SQL is required.
- SQL: be able to manipulate or build automation scripts using sql
- Know how SQL and Kafka works; concepts.
- 7 years exp
- Strong Communication: Ability to articulate technical concepts: What is your choice of technology and be able to provide the reasons as to why for technical decisions.
Desirable:
- Domain: Geospatial tools, or working with geospatial data or environmental or Ag data
- Machine learning – exploring some projects around building some analytics solutions feature engineering to support the modeling teams.
- Data preprocess – like feature engineering , preparing data
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