Data Engineer

Compunnel

$110K — $130K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience with Azure and Azure Databricks.
  • Proficiency in data engineering practices including ETL/ELT and data modeling.
  • Experience handling large-scale datasets and distributed data processing systems.
  • Familiarity with AI technologies, especially Large Language Models (LLMs).
  • Strong SQL capabilities for data manipulation and transformation tasks.
  • Excellent problem-solving and analytical skills applicable to data issues.
  • Proven ability to communicate effectively with business stakeholders, including executives.

Responsibilities

  • Design and maintain scalable data pipelines utilizing Azure and Databricks.
  • Optimize data ingestion, transformation, and modeling processes for efficiency.
  • Support integrations involving AI and LLM technologies.
  • Collaborate with business teams to define and deliver data solutions.
  • Enhance data workflows ensuring performance and reliability.
  • Ensure adherence to data quality, governance, and security standards across platforms.
  • Document technical specifications and data engineering processes to support transparency.

Benefits

  • Flexible working hours to support work-life balance.
  • Opportunity to work on cutting-edge AI and data initiatives.
  • Collaborative work environment with cross-functional teams.
  • Possibility to influence and contribute to strategic data solutions.
  • Support for continuous learning and professional development.
Full Job Description
Job Summary
We are seeking a hands-on Data Engineer to support AI and data initiatives focused on Azure and Databricks. The ideal candidate will have strong experience building scalable data pipelines, processing large datasets, and supporting AI/LLM integrations. This role requires an independent contributor who can work directly with business stakeholders and deliver high-quality data solutions with minimal ramp-up time.

Key Responsibilities
• Design, develop, and maintain scalable data pipelines using Azure and Databricks.
• Build and optimize data ingestion, transformation, and data modeling processes for large datasets.
• Support AI and data engineering initiatives, including integration with LLM-based solutions.
• Collaborate with business stakeholders to understand requirements and deliver data-driven solutions.
• Develop and optimize data workflows for performance, scalability, and reliability.
• Ensure data quality, governance, and security across enterprise data platforms.
• Troubleshoot and resolve data pipeline and platform issues.
• Document technical solutions, data models, and engineering processes.
• Work independently while collaborating with cross-functional business and technical teams.

Required Qualifications
• Strong hands-on experience with Azure and Azure Databricks.
• Experience with data engineering, data ingestion, ETL/ELT, and data modeling.
• Experience working with large-scale datasets and distributed data processing.
• Exposure to AI, Large Language Models (LLMs), or AI integration initiatives.
• Strong SQL and data transformation skills.
• Excellent analytical, problem-solving, and troubleshooting abilities.
• Strong communication skills with the ability to work directly with business stakeholders, including executive leadership.
• Ability to work independently with minimal supervision.

Preferred Qualifications
• Experience in the healthcare industry.
• Knowledge of 340B pharmacy programs or pharmacy data.
• Experience with full-stack development.
• Experience supporting AI-driven data platforms and analytics solutions.
• Strong consulting mindset with the ability to quickly adapt to new environments.

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