Back to Browse Jobs
DarioHealth
Create a free account
One signup unlocks everything for this job:
- Apply to this job and track your application
- See your personalized profile match score
- Generate an AI cover letter for this role
Haryana · On-site · 6-9 Yrs · Sep 25
4 views
Healthcare Services & Hospitals · 51 to 200 Employees · New York, US
1 open role0 posted in 7d1 in 30d
Work-life balance 3.5Compensation & benefits 3.4Culture & values 3.3
Hiring: Engineering
What employees say
+ Good technology learning scope and good collaboration.
− They don’t have funds to keep bare minimum resources for the project delivery. They fire valuable people and give them only 1 month severance.
More reviews on the company profile.
Interview experience · Data Engineer
Total three rounds. One technical,one managerial and one round with hr. In technical round, i got asked sql, python snowflake. Dbt and airflow in case you worked on it. Window function, joins, group by
Easy difficulty · India · 8 reports
More interview insightsJob description
Overview
We are on a mission to make better health easy.
Responsibilities
- 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.
- 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.
- 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
- Design and execute validation and testing processes across pipelines, transformations, dashboards, and business logic.
- Ensure compliance with security, governance, privacy, and regulatory standards.
Qualifications
- Strong understanding of data warehousing, dimensional modeling, and modern data architecture principles.
- 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.
- Familiarity with LLM ecosystems, vector databases, embeddings, and AI orchestration frameworks.
- Healthcare or health-tech industry experience is a plus.
Verify Python for this role
Free PRACTICE for Python adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify Python free →Want match scores and deeper insight? Create a free candidate profile
Job application FAQ
Last updated 4 October 2026
- How do I apply for Senior AI Data Engineer at DarioHealth?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. DarioHealth may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Senior AI Data Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Senior AI Data Engineer remote or on-site in Haryana?
- This listing is marked on_site with location Haryana. Confirm details on the job description before applying.
- What skills matter for this Senior AI Data Engineer role at DarioHealth?
- This is a senior Senior AI Data Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.