Data Engineer /Data Platform Engineer

hi,

Data Platform Engineer

Duration: 6-12 months extensions

Location: Remote (PST time zone) 
Responsibilities:

·        Architect, create, and deploy necessary infrastructure within our hybrid-cloud environment to scale data applications and pipelines

·        Accountable for the technical decision making and owning engineering execution in the team as it relates to data

·        Engineering and DevOps responsibilities

·        Understand current technical bottlenecks and champion solutions for long-term scalability

·        Developing and integrating best practices to increase the quality and velocity of deployments

·        Partnering with engineering teams to evangelize and improve standardized Release Engineering processes

·        Build and maintain data platform codebase and iterate over its lifecycle for scalability and adoption org-wide

·        Working in an agile culture

 
Requirements:

·        B.S/M.S. in Computer Sciences or equivalent field, and 4 years of relevant experience with data platform engineering

·        Expertise in designing, building, and maintaining Kubernetes clusters and containers as it relates to Data Pipelines and CI/CD processes

·        Expertise configuring and maintaining CI/CD pipelines (for this role, we would be needing CI/CD processes for our IaC in AWS using Terraform, dbt deployment, and our data platform)

·        Experience in data orchestration tools like Airflow

·        Experience with public cloud providers such as Google Cloud, AWS, Azure (certifications are a plus)

·        High fluency with Python and other common programming languages

·        Experience with logging, monitoring and alerting systems and tools

·        Excellent debugging skills in a Linux environment

·        Experience with credential management in code

·        Experience with version control systems (GitHub, Stash etc..) and deployment tools

 
Preferred Platform Experience:

·        Snowflake, BigQuery (or similar data warehouse)

·        Apache Airflow (or similar orchestration tools)

·        dbt and ELT paradigms

·        Dataiku or SageMaker AI/ML platform

·        Jenkins or similar CI/CD

·        GitHub, GitLab, BitBucket, etc.

·        Candidate filtering

·        Find candidates who have experience in cloud/hybrid deployments using Kubernetes and scalable cloud infrastructure.

·        Experience with Airflow, AWS, dbt, data pipelines, and Snowflake (or very similar) a must.

·        Experience with Dataiku/SageMaker is a huge plus