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Full-Stack Data Engineer

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Key Responsibilities

  • Design, develop, and optimize scalable ETL/ELT pipelines using Databricks, SQL, Python, and Spark.
  • Build and maintain robust data models and data products that enable analytics, automation, and business decision-making.
  • Ensure data quality, reliability, and maintainability through monitoring, testing, documentation, and CI/CD best practices.
  • Partner with Data Product Owners (DPOs) and business stakeholders to rapidly translate requirements into production-ready solutions.
  • Design, develop, and deploy AI agents and agentic workflows to automate business and engineering processes.
  • Leverage AI-assisted development tools to accelerate solution design, coding, testing, troubleshooting, and optimization.
  • Evaluate and adopt emerging AI and data technologies to enhance productivity, data accessibility, and solution delivery.


Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field.
  • Strong experience in ETL/ELT development, data modeling, and data quality management.
  • Proficiency in SQL and Python, with hands-on experience in Databricks and Spark.
  • Experience developing AI agents, LLM-based applications, workflow automation, or agentic systems.
  • Familiarity with modern AI development frameworks, APIs, and AI-assisted engineering tools.
  • Strong problem-solving, communication, and stakeholder management skills.
  • Ability to work independently and deliver high-quality solutions in a fast-paced environment.

See also

Full-Stack jobs by country — openings, pay and top skills →

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