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Suki AI

AI voice assistant for clinical documentation

Data Engineer

Data EngineeringPosted on Nov 12
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Three to five years of experience in analytics engineering or data engineering, ideally in a B2B SaaS or Customer Success environment.
  • Expert proficiency in SQL and dbt.
  • Experience modeling complex semi-structured data, including JSON or FHIR, into analytical tables in BigQuery or Snowflake.
  • Hands-on experience with ELT tools such as Fivetran or Airbyte and orchestration tools such as Airflow or dbt Cloud.
  • Ability to manage data flow from raw ingestion through the final business intelligence layer.
  • Working knowledge of Salesforce data schemas, including Objects, Leads, and Opportunities.
  • Familiarity with Tableau or Looker for optimizing data sources for performance.
  • Understanding of data governance, testing with dbt tests, and version control with Git.
  • Practical expertise using Python to create bespoke API integrations, automate workflows, and develop operational data processes beyond standard connectors.

Responsibilities

  • Design, maintain, and optimize data architecture in BigQuery to support analytics, automation, and business intelligence.
  • Build and manage ETL/ELT pipelines between BigQuery, Salesforce, Gainsight, and other systems.
  • Set up and manage Google Cloud Platform infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows, to automate ingestion and transformation.
  • Create and maintain data models and standardized BigQuery tables for the Customer Success organization.
  • Document data architecture, pipelines, and automation workflows to support maintainability and reproducibility.
  • Own end-to-end data ingestion using modern ELT tools and Reverse ETL, prioritizing configuration-based connectors over custom Python scripts where suitable.
  • Implement automated data quality testing suites using dbt tests and configure alerts for pipeline failures or data freshness delays.
  • Partner with Analytics to structure data models for high-performance dashboard queries.
  • Collaborate with Customer Success, Product, Finance, and Sales to align data definitions, access, and governance standards.
  • Identify data quality issues, redundancies, and inefficiencies, and lead remediation efforts.
  • Implement data profiling and testing to detect schema drift, enforce data hygiene, and handle missing or incomplete values before data is loaded.
  • Partner with clinical and analytics teams to standardize client metric definitions and map data from different health systems into a consistent format.
  • Design flexible ingestion pipelines for semi-structured data such as JSON and new metrics without breaking downstream models.

Desired Qualifications

  • Experience in a B2B SaaS or Customer Success environment.
  • Experience with Reverse ETL tools such as Hightouch or Census.

About the Company

Suki AI

AI voice assistant for clinical documentation

Suki AI provides an AI-powered voice assistant for healthcare professionals to handle clinical documentation. It works by capturing notes through ambient, dictation, or command modes and can synchronize with leading Electronic Health Record (EHR) systems, allowing notes to be started in the EHR and finished in Suki or vice versa. The product reduces time spent on documentation by up to 72%, freeing clinicians to spend more time with patients. Suki operates on a subscription model: a per-user-per-month fee with an additional charge for an enterprise-grade clinical documentation app; EHR integration is not included in the base subscription. The company differentiates itself through EHR integration, flexible note-taking modes, and seamless cross-system note workflow, targeting healthcare professionals who want to streamline documentation. The goal is to increase clinicians’ time with patients by making documentation faster and easier, improving efficiency in clinical settings.

Company size
201-500
Company stage
Series E
Total funding
$255M
Headquarters
Redwood City, CA
Founded
2017

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