GCP CloudOps Engineer - Maryland Heights, United States - NetEffects

Description

W2 Candidates Only 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:

1. Mainly work on deploying and maintain cloud infrastructures.
2. Adding observabilities to their pipelines & services
3. ID opportunities for workflow optimization & cloud cost effectiveness/savings.
4. 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 thats 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