Senior AI Data Engineer

dariohealth

Gurugram 6 Years Exp Posted 6h ago

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:

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:

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 methodol