Senior AI Data Engineer

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 seeking an experienced Senior AI Data Engineer to join our Data organization. This role is designed for engineers who thrive in an AI-first, cross-functional environment and want to own the full lifecycle of data solutions — from infrastructure and pipelines to analytics, dashboards, automation, and business impact.

The Senior AI Data Engineer will operate within a domain ownership model, taking responsibility for both technical execution and business-facing outcomes within rotating organizational domains such as Clinical, Finance, Product Analytics, Enrollment, AI Infrastructure, Data Infrastructure, and QA.

This is not a traditional siloed analyst or engineering role. We are looking for individuals who can combine technical depth, business understanding, AI-assisted execution, and product-oriented thinking into a single end-to-end ownership mindset.

The ideal candidate is highly technical, proactive, AI-oriented, comfortable working across multiple layers of the stack, and capable of independently driving initiatives from concept through delivery.

Only candidates currently residing in Gurugram, or those willing to relocate, will be considered

What You Will Do

End-to-End Data Solution Ownership

• Own the full lifecycle of data solutions including ingestion, transformation, modeling, visualization, automation, monitoring, and stakeholder delivery.
• Design, develop, and maintain scalable ETL/ELT pipelines, data warehouses, semantic layers, and near real-time data flows.
• Build and maintain dashboards, operational reporting, KPI tracking, and business-facing analytical products.
• Collaborate closely with Product, Design, R&D, Analytics, Marketing, Operations, and Business stakeholders to translate requirements into scalable technical solutions.
• Drive initiatives independently from planning and architecture through deployment and operational support.

AI-First Engineering & Automation

• Leverage AI-assisted development workflows to accelerate execution, improve code quality, and optimize operational efficiency.
• Design and maintain AI-enabled workflows including prompt pipelines, automated enrichment processes, vector integrations, and LLM-assisted tooling where applicable.
• Evaluate and adopt emerging AI/GenAI technologies to improve engineering velocity and organizational scalability.
• Contribute to automation-first engineering practices across development, QA, monitoring, and documentation workflows.
• Utilize Git-based workflows and modern software engineering practices as part of daily execution.

Data Engineering & Infrastructure

• Develop scalable and reliable data pipelines using modern orchestration and transformation frameworks.
• Optimize existing infrastructure for performance, cost efficiency, scalability, and reliability.
• Build and maintain data quality validation frameworks, monitoring systems, and operational alerting processes.
• Support both batch and near real-time processing architectures.
• Contribute to future-state architecture decisions across data platform and AI infrastructure initiatives.
• Maintain technical documentation including architecture diagrams, data dictionaries, SOPs, and operational playbooks.

Analytics & Business Partnership

• Partner directly with business stakeholders to understand operational challenges and identify opportunities for automation and insight generation.
• Own business-critical KPIs, reports, and dashboards.
• Surface actionable insights proactively to support strategic and operational decision-making.
• Support experimentation frameworks, metric validation, and analytical initiatives.
• Ensure alignment between business expectations, data definitions, and technical implementation.

Domain Ownership & Rotation Model

• Operate within a rotating domain ownership structure designed to increase business understanding and reduce organizational silos.
• During each rotation cycle:

1. Own the domain roadmap
2. Drive technical initiatives
3. Support stakeholders
4. Present progress and business impact
5. Perform structured knowledge handoffs

Quality, Compliance & Delivery

• Design and execute validation and testing processes across pipelines, transformations, dashboards, and business logic.
• Ensure compliance with security, governance, privacy, and regulatory standards.
• Participate in PR reviews, technical reviews, and collaborative engineering governance processes.
• Work in Agile development environments with strong ownership and accountability expectations.
• Contribute to engineering standards, best practices, and continuous improvement initiatives.

Requirements

• 6+ years of hands-on experience in Data Engineering, Analytics Engineering, or similar technical data roles.
• Strong proficiency in Python and SQL.
• Experience with Snowflake and dbt.
• Experience developing scalable ETL/ELT pipelines.
• Strong understanding of data warehousing, dimensional modeling, and modern data architecture principles.
• Experience with orchestration frameworks such as Airflow.
• Experience with Git, CI/CD workflows, and collaborative development practices.
• Experience with dashboarding and analytical tooling such as Tableau, Streamlit, or Power BI.
• Familiarity with AI-assisted development workflows and modern GenAI tooling.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management abilities.
• Ability to independently manage initiatives and operate in cross-functional environments.
• Experience working in Agile methodologies.

Preferred Qualifications

• Experience with AWS or other cloud-native data technologies.
• Experience with Kafka, Spark, Flink, or streaming architectures.
• Familiarity with LLM ecosystems, vector databases, embeddings, and AI orchestration frameworks.
• Experience with QA automation and data testing frameworks.
• Experience with Fivetran or modern ingestion platforms.
• Experience supporting production analytics and operational reporting systems.
• Healthcare or health-tech industry experience is a plus.

***DarioHealth promotes diversity of thought, culture and background, which connects the entire Dario team. We believe that every member on our team enriches our diversity by exposing us to a broad range of ways to understand and engage with the world, identify challenges, and to discover, design and deliver solutions. We are passionate about building and sustaining an inclusive and equitable working and learning environments for all people, and do not discriminate against any employee or job candidate.​***