AI Data Engineer - Early Career

At Dario, Every Day is a New Opportunity to Make a Difference.

We are on a mission to make better health easy. Every day our employees contribute to this mission and help hundreds of thousands of people around the globe improve their health. How cool is that? We are looking for passionate, smart, and collaborative people who have a desire to do something meaningful and impactful in their career.

We are looking for an enthusiastic AI Data Engineer to join our growing Data organization. This is an excellent opportunity for a recent graduate, final-year student (available for full-time employment), or an engineer with up to one year of professional experience who is passionate about data, AI, and building modern data platforms.

You'll work alongside experienced Data Engineers, Analytics Engineers, and AI specialists to build scalable data pipelines, develop analytics solutions, and explore how Generative AI can improve engineering productivity and business processes.

The AI Data Engineer will work within our domain ownership model, contributing to both technical execution and business outcomes across rotating organizational domains such as Clinical, Finance, Product Analytics, Enrollment, AI Infrastructure, Data Infrastructure, and QA. Through these rotations, you'll gain broad exposure to different parts of the business while developing both technical expertise and domain knowledge.

This is not a traditional siloed analyst or engineering role. We are looking for individuals who are eager to develop a combination of technical skills, business understanding, AI-assisted development practices, and product-oriented thinking. With guidance and mentorship, you'll have the opportunity to contribute across the full lifecycle of data solutions—from data ingestion and transformation to analytics, automation, and business insights.

The ideal candidate is technically curious, proactive, passionate about AI, comfortable learning across multiple layers of the data stack, and excited to grow into an engineer who can take increasing ownership of projects from concept through delivery.

What You'll Do

Build Data Solutions

• Assist in designing, building, and maintaining scalable ETL/ELT pipelines and data workflows.
• Write clean, efficient, and maintainable Python and SQL code.
• Support the development and maintenance of data models, semantic layers, and data warehouses.
• Help monitor data quality, troubleshoot pipeline issues, and improve data reliability.
• Contribute to data documentation, including data dictionaries and technical documentation.
  
  

• Build dashboards, reports, and KPI tracking solutions that enable data-driven decision-making.
• Collaborate with Product, Engineering, Clinical, Finance, Operations, and other business teams to understand data and reporting requirements.
• Perform exploratory data analysis to identify trends, insights, and opportunities for improvement.
• Assist in validating business metrics and supporting analytical initiatives.
  
  

• Leverage AI-assisted development tools to improve productivity, code quality, and engineering efficiency.
• Learn and contribute to AI-enabled workflows, automation, and modern GenAI-powered engineering practices.
• Explore emerging AI technologies and identify opportunities to improve internal engineering processes.
• Participate in automation initiatives that reduce manual effort across the organization.
  
  

• Learn modern data engineering best practices and contribute to scalable data infrastructure.
• Support orchestration workflows and scheduled data processing.
• Participate in testing, monitoring, and validation of data pipelines.
• Contribute to improving platform reliability, scalability, and operational excellence.
  
  

• Work closely with experienced engineers through mentorship and code reviews.
• Participate in Agile ceremonies including sprint planning, stand-ups, retrospectives, and technical discussions.
• Continuously learn new technologies and contribute ideas for improving our data platform and engineering practices.
• Take increasing ownership of projects and responsibilities as your skills grow.
  
  

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Mathematics, Statistics, or a related technical field.
• Final-year students who can commit to full-time employment upon graduation are encouraged to apply.
  
  

• 0–1 year of professional experience in Data Engineering, Software Engineering, Analytics Engineering, Data Analytics, or a related technical role.
• Relevant internships, military technology experience, academic projects, research work, or open-source contributions are highly valued.
  
  

• Strong knowledge of SQL.
• Programming experience with Python.
• Understanding of relational databases and data modeling fundamentals.
• Basic understanding of ETL/ELT concepts.
• Familiarity with Git and version control.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Passion for learning new technologies and solving complex problems.
  
  

• Internship or project experience involving data engineering or analytics.
• Exposure to Snowflake, dbt, Airflow, or similar modern data technologies.
• Experience building dashboards using Tableau, Power BI, Looker, or similar BI tools.
• Familiarity with AWS, Azure, or Google Cloud Platform.
• Exposure to AI coding assistants such as GitHub Copilot, ChatGPT, Cursor, Claude, or similar tools.
• Basic understanding of Large Language Models (LLMs), machine learning, or Generative AI concepts.
• Experience with APIs and JSON data.
• Familiarity with software engineering best practices, testing, and CI/CD concepts.
• Healthcare or HealthTech experience is a plus but not required.
  
  

• Modern Data Engineering
• Python & SQL at scale
• Snowflake
• dbt
• Airflow
• Cloud Data Platforms
• Data Modeling
• Dashboard Development
• AI-assisted Software Development
• Data Quality & Monitoring
• Generative AI Applications
• Cross-functional Product & Business Collaboration
  
  

• Work with an experienced Data & AI team in a collaborative, AI-first environment.
• Receive mentorship from experienced engineers and technical leaders.
• Build solutions that directly improve healthcare outcomes for patients around the world.
• Gain hands-on experience with modern cloud technologies, data platforms, and AI tools.
• Work across multiple business domains and develop both technical and business expertise.
• Enjoy significant opportunities for learning, ownership, and career growth in a fast-growing HealthTech company.