AI Data Engineer

Dario Health Corp.; Gurugram District; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Dario Health Corp. is seeking an experienced AI Data Engineer to improve health solutions and drive impactful data initiatives. This role involves owning the entire lifecycle of data solutions, working across multiple domains, and collaborating with various business functions.

The ideal candidate has over 4 years of experience in Data Engineering, strong skills in Python and SQL, and is comfortable leveraging AI technologies. The position focuses on innovation and requires a proactive approach to solving complex challenges.

Qualifications

• 4+ years of hands-on experience in Data Engineering or Analytics Engineering.
• Strong understanding of data warehousing and modern data architecture principles.
• Excellent communication and stakeholder management abilities.

Responsibilities

• Own the full lifecycle of data solutions including ingestion, transformation, and visualization.
• Design, develop, and maintain scalable ETL/ELT pipelines.
• Collaborate closely with business stakeholders to translate requirements into scalable technical solutions.

Skills

Python

SQL

Data Engineering

Analytics Engineering

Communication

Stakeholder Management

Problem Solving

Tools

Snowflake

dbt

Airflow

Tableau

Power BI

Git

Job description

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 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 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

• 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.
• 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.
• 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:
• Own the domain roadmap
• Drive technical initiatives
• Support stakeholders
• Present progress and business impact
• 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.

What you have

• 4+ 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.
• 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.***