Location: Remote (PST working hours)

Duration: 6 months contract (possibility of extension)

Pay rate: $77.46/hr on W2

Job Summary:

The main function of the Data Engineer is to develop, evaluate, test and maintain architecture and data solutions within our organization. The typical Data Engineer executes plans, policies, and practices that control, protect, deliver, and enhance the value of the organization’s data assets.

This is a data engineer role with heavy SQL and pipeline transformation work, supporting ML feature creation and automation. The most important qualities are SQL strength, ability to work independently, and agility in fast-changing environments.

Job Responsibilities:

• Manage data engineering projects through the full cycle.

• Identify and underline business initiatives from a data engineering perspective

• Design, construct, install, test and maintain highly scalable data management systems.

• Ensure systems meet business requirements and industry practices.

• Design, implement, automate and maintain large scale enterprise data ETL processes.

• Build high-performance algorithms, prototypes, predictive models and proof of concepts.

Skills:

• Ability to work as part of a team, as well as work independently or with minimal direction.

• Excellent written, presentation, and verbal communication skills.

• Collaborate with data architects, modelers and IT team members on project goals.

• SQL and data workflow skills

Education/Experience:

• Bachelor's degree in technical fields such as computer science, computer engineering or related field required.

Candidate Profile (Ideal Fit):

• Background in hardcore technical/data engineering environments (not banking/legacy industries).

• Familiar with cloud infrastructure, orchestration layers, and modern data workflows.

• Agile mindset: comfortable with frequent direction changes and ambiguous problem spaces.

• Excited by:

 Direct impact of work (features/data transformations directly influence models).

 Exposure to state-of-the-art ML models and cutting-edge automation.

 Opportunity to work on industry-first transitions in data and ML infrastructure.

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