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Data Engineer – Azure Databricks & Python (Remote)

BairesDev · District Capital

Remote
Remote Mid 🇬🇧 English
Azure Databricks Python SQL LLM APIs Cloud-native data architecture Data governance Security best practices

Descripcion del puesto

About the role

We are looking for a Data Engineer to design and develop scalable data pipelines using Azure Databricks and Python. The role focuses on integrating AI and large‑language‑model APIs into data workflows to automate classification and generate insights.

Key responsibilities

  • Design, build and optimise end‑to‑end data pipelines and Lakehouse architectures on Azure Databricks.
  • Integrate LLM APIs and machine‑learning models into processing streams for automated classification.
  • Write and maintain high‑quality Python code and SQL procedures for data transformation and ingestion.
  • Collaborate with AI and product teams to deliver data‑driven solutions that add business value.
  • Monitor pipeline performance, troubleshoot issues and ensure reliability and scalability in a distributed cloud environment.
  • Implement data‑governance and security best practices to maintain data integrity and compliance.

Required profile

  • Minimum 4 years of experience in data engineering, machine‑learning engineering or software engineering.
  • Proven expertise with Azure Databricks and Python for building data pipelines.
  • Experience integrating ML/AI solutions and LLM APIs into automated workflows.
  • Advanced proficiency in English.

Required skills

  • Azure Databricks
  • Python
  • SQL
  • LLM APIs
  • Machine‑learning model integration
  • Cloud‑native data architecture
  • Data governance and security practices

What we offer

  • 100 % remote work from anywhere.
  • Competitive compensation in USD or local currency.
  • Provided hardware and software setup for home office.
  • Flexible schedule and paid parental leave, vacations and holidays.
  • Multicultural environment with mentorship, promotion and skill‑development opportunities.

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BairesDev

District Capital