Data Engineer

Globaldev Group

United States

Remote

USD 110,000 - 180,000

Full time

8 days ago
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Benefits offered by this job

20 days vacation
Public holidays
Mobilization reservation for Ukrainian
Bookkeeping by accountant
HR team support

Job summary

Globaldev Group is seeking a Backend Data Engineer with 3+ years of experience to join a fast-paced team building modern data platforms and AI-assisted development tools.

You will design and maintain scalable data pipelines, work with Snowflake and Databricks, and leverage GenAI tools to accelerate workflows. The role emphasizes ownership, collaboration, and a product-oriented mindset across engineering, analytics, and product teams.

Qualifications

  • 4+ years experience in Data or Backend Engineering.
  • Strong SQL, dbt, data modeling, and data pipelines experience.
  • Experience with Snowflake and/or Databricks and orchestration tools.
  • Comfort adopting GenAI tools in daily engineering.

Responsibilities

  • Design, build, and maintain scalable data pipelines and backend data infrastructure.
  • Develop transformations with dbt and cloud platforms like Snowflake/Databricks.
  • Manage workflow orchestration for reliable production data processes.
  • Create internal data apps with Streamlit.
  • Collaborate with Data Product Managers to translate requirements.
  • Team up across engineering, analytics, and product; challenge assumptions.
  • Leverage GenAI tools to accelerate engineering workflows.
  • Own projects from design through deployment and improvement.

Skills

dbt
SQL
data modeling
data pipelines
communication
ownership
teamwork
GenAI tools
independence

Tools

Snowflake
Databricks
Orchestration tools
Streamlit

Job description

We are looking for a Backend Data Engineer with 3+ years of experience to join a fast-paced organization working with modern data platforms, AI-assisted development tools, and rapidly evolving technologies. The ideal candidate combines strong engineering skills with ownership, collaboration, and a product-oriented mindset.

Responsibilities
  • Design, build, and maintain scalable data pipelines, models, and backend data infrastructure.
  • Develop and optimize transformation workflows using dbt and cloud data platforms such as Snowflake and/or Databricks.
  • Build and manage workflow orchestration for reliable, production-grade data processes.
  • Create internal data applications and tooling using technologies such as Streamlit.
  • Work closely with Data Product Managers to translate business and product requirements into practical technical solutions.
  • Collaborate across engineering, analytics, and product teams; ask the right questions, challenge assumptions when needed, and help shape solutions.
  • Use modern GenAI development tools such as Cursor, Snowflake CoWork, Codex, Claude Code, and similar tools to accelerate engineering workflows.
  • Take ownership from design through implementation, deployment, and continuous improvement.
Requirements
  • 4+ years of experience in Data Engineering, Backend Engineering, or a related role.
  • Strong hands-on experience with dbt, SQL, data modeling, and data pipelines.
  • Experience with Snowflake and/or Databricks and modern orchestration tools.
  • Strong communication, teamwork, ownership, reliability, and professional work ethic.
  • Ability to operate independently in a dynamic environment where requirements may evolve quickly.
  • Comfort adopting new technologies and using GenAI tools as part of the day-to-day engineering workflow.
Would be a plus
  • Hands-on experience with Python, REST APIs, or backend service development.
  • Experience with Streamlit or similar frameworks for data-driven applications.
What we offer
  • Comfortable environment, challenging tasks and a long-term interesting project;
  • Covered 20 days of vacation;
  • Public holidays;
  • Mobilization reservation available upon successful completion of the probation period (for Ukrainian colleagues);
  • Bookkeeping by a professional accountant;
  • Help and support from our caring HR-team.
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