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Data Engineer

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

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Live
First seen by us
Nov 14, 2026today
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1
Employer says posted
Nov 12, 2026

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How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 56.

From 13,630 similar postings that came down. Coming down is not always a hire.

Suki is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Airbyte
  • BigQuery
  • Census
  • dbt
  • Fivetran
  • GCP
  • Hightouch
  • Looker
  • Snowflake
  • Tableau
  • Airflow
Where the posting names them
Are you a Data Engineer looking to make a real impact? We are looking for a founding Data Engineer to architect the modern data stack that powers our Customer Success organization. In this role, you will move beyond simple data maintenance to design the Semantic Layer—the "Single Source of Truth"—that defines how Suki measures value, adoption, and retention. You will own the end-to-end data lifecycle: orchestrating automated ingestion (ELT), modeling complex healthcare data in BigQuery using dbt, and optimizing data delivery for high-performance BI in Tableau. This is a high-visibility role for a builder who wants to replace manual processes with scalable, engineering-grade data infrastructure. A key part of this role includes automating data pipelines across platforms such as Salesforce, Gainsight, and external customer signals—leveraging APIs, Python, and emerging AI tools to replace manual reporting with scalable, engineering-grade infrastructure. Here's a sneak peek of what you'll be doing:
Automation & Integration - Manage Data Pipelines: Own the end-to-end data ingestion process using modern ELT tools and Reverse ETL. Prioritise configuration-based connectors over custom Python scripts to ensure long-term maintainability. - Data Quality & Observability: Implement automated testing suites (using dbt tests) to detect data anomalies before they reach dashboards. Configure alerts to notify the team of pipeline failures or freshness delays.
- BI & Quality: Familiarity with Tableau (or Looker) to optimize data sources for performance. Strong understanding of data governance, testing (dbt tests), and version control (Git). - Mindset: Proactive problem solver who focuses on maintainable, scalable architecture over one-off scripts. Excellent attention to detail. Deep, practical expertise in using Python to create bespoke API integrations, automate workflows, and develop operational data processes, exceeding the capabilities of standard connectors. Tell me more about Suki
- Experience: 3–5 years in Analytics Engineering or Data Engineering, ideally within a B2B SaaS or Customer Success environment. - Core Stack: Expert proficiency in SQL and dbt. Demonstrated experience modeling complex, semi-structured data (JSON/FHIR) into clean analytical tables in BigQuery (or Snowflake). - Data Pipeline Management: Hands-on experience with ELT tools (Fivetran, Airbyte) and orchestration (Airflow, dbt Cloud). Ability to manage data flow from raw ingestion to the final BI layer.
- Core Stack: Expert proficiency in SQL and dbt. Demonstrated experience modeling complex, semi-structured data (JSON/FHIR) into clean analytical tables in BigQuery (or Snowflake). - Data Pipeline Management: Hands-on experience with ELT tools (Fivetran, Airbyte) and orchestration (Airflow, dbt Cloud). Ability to manage data flow from raw ingestion to the final BI layer. - CRM & Systems: Working knowledge of Salesforce data schemas (Objects, Leads, Opportunities). Experience with Reverse ETL (Hightouch/Census) to sync data back to business tools is a strong plus.
Data Architecture & Infrastructure - Design, maintain, and optimize a clean, well-structured data architecture in BigQuery to support analytics, automation, and business intelligence. - Build and manage ETL/ELT pipelines between BigQuery, Salesforce, Gainsight, and other systems for seamless, scalable data flow.
- Design, maintain, and optimize a clean, well-structured data architecture in BigQuery to support analytics, automation, and business intelligence. - Build and manage ETL/ELT pipelines between BigQuery, Salesforce, Gainsight, and other systems for seamless, scalable data flow. - Set up and manage GCP infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows, to automate ingestion and transformation.
- Set up and manage GCP infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows, to automate ingestion and transformation. - Create and maintain data models and standardized tables in BigQuery to support analytical needs across the Customer Success organization. - Document data architecture, pipelines, and automation workflows to ensure maintainability and reproducibility.
- Data Pipeline Management: Hands-on experience with ELT tools (Fivetran, Airbyte) and orchestration (Airflow, dbt Cloud). Ability to manage data flow from raw ingestion to the final BI layer. - CRM & Systems: Working knowledge of Salesforce data schemas (Objects, Leads, Opportunities). Experience with Reverse ETL (Hightouch/Census) to sync data back to business tools is a strong plus. - BI & Quality: Familiarity with Tableau (or Looker) to optimize data sources for performance. Strong understanding of data governance, testing (dbt tests), and version control (Git).
- Manage Data Pipelines: Own the end-to-end data ingestion process using modern ELT tools and Reverse ETL. Prioritise configuration-based connectors over custom Python scripts to ensure long-term maintainability. - Data Quality & Observability: Implement automated testing suites (using dbt tests) to detect data anomalies before they reach dashboards. Configure alerts to notify the team of pipeline failures or freshness delays. - BI Performance Tuning: Partner with Analytics to structure data models ("One Big Table") that ensure sub-second query performance for dashboards. Collaboration & Governance
- CRM & Systems: Working knowledge of Salesforce data schemas (Objects, Leads, Opportunities). Experience with Reverse ETL (Hightouch/Census) to sync data back to business tools is a strong plus. - BI & Quality: Familiarity with Tableau (or Looker) to optimize data sources for performance. Strong understanding of data governance, testing (dbt tests), and version control (Git). - Mindset: Proactive problem solver who focuses on maintainable, scalable architecture over one-off scripts. Excellent attention to detail. Deep, practical expertise in using Python to create bespoke API integrations, automate workflows, and develop operational data processes, exceeding the capabilities of standard connectors.
- Build and manage ETL/ELT pipelines between BigQuery, Salesforce, Gainsight, and other systems for seamless, scalable data flow. - Set up and manage GCP infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows, to automate ingestion and transformation. - Create and maintain data models and standardized tables in BigQuery to support analytical needs across the Customer Success organization.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

What we want to accomplish and why we need you

Suki is a leading technology company that provides AI voice solutions for healthcare. Its mission is to reimagine the healthcare technology stack, making it invisible and assistive to lift the administrative burden from clinicians. Its flagship product is Suki Assistant, an AI assistant thatuses generative AI to automatically create clinical documentation by ambiently listening to patient-clinician conversations. Suki helps clinicians complete notes 72% faster on average, assists with other tasks including coding and answering questions, and generates incremental revenue for organizations, delivering a 9X ROI in year 1. Suki also offers its proprietary AI and speech platform, Suki Platform, to partners who want to create best-in-class ambient and voice experiences for their solutions. Clinicians that use Suki already spend over 70% less time on administrative tasks, and we’re striving to do even better. Come and join us!

We are a user-driven company and are committed to making sure every pixel of our product is in service of the doctors. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine. We’re confident enough to move fast and talented enough not to break things.

Are you a Data Engineer looking to make a real impact?

We are looking for a founding Data Engineer to architect the modern data stack that powers our Customer Success organization. In this role, you will move beyond simple data maintenance to design the Semantic Layer—the "Single Source of Truth"—that defines how Suki measures value, adoption, and retention. You will own the end-to-end data lifecycle: orchestrating automated ingestion (ELT), modeling complex healthcare data in BigQuery using dbt, and optimizing data delivery for high-performance BI in Tableau. This is a high-visibility role for a builder who wants to replace manual processes with scalable, engineering-grade data infrastructure. A key part of this role includes automating data pipelines across platforms such as Salesforce, Gainsight, and external customer signals—leveraging APIs, Python, and emerging AI tools to replace manual reporting with scalable, engineering-grade infrastructure.

Here's a sneak peek of what you'll be doing:

Data Architecture & Infrastructure

  • Design, maintain, and optimize a clean, well-structured data architecture in BigQuery to support analytics, automation, and business intelligence.
  • Build and manage ETL/ELT pipelines between BigQuery, Salesforce, Gainsight, and other systems for seamless, scalable data flow.
  • Set up and manage GCP infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows, to automate ingestion and transformation.
  • Create and maintain data models and standardized tables in BigQuery to support analytical needs across the Customer Success organization.
  • Document data architecture, pipelines, and automation workflows to ensure maintainability and reproducibility.

Automation & Integration

  • Manage Data Pipelines: Own the end-to-end data ingestion process using modern ELT tools and Reverse ETL. Prioritise configuration-based connectors over custom Python scripts to ensure long-term maintainability.
  • Data Quality & Observability: Implement automated testing suites (using dbt tests) to detect data anomalies before they reach dashboards. Configure alerts to notify the team of pipeline failures or freshness delays.
  • BI Performance Tuning: Partner with Analytics to structure data models ("One Big Table") that ensure sub-second query performance for dashboards. Collaboration & Governance
  • Collaborate cross-functionally with Customer Success, Product, Finance, and Sales to align on data definitions, access, and governance standards.
  • Proactively identify data quality issues, redundancies, or inefficiencies, and lead remediation efforts to maintain data integrity. Collaboration & Governance
  • Collaborate cross-functionally with Customer Success, Product, Finance, and Sales to align on data definitions, access, and governance standards.
  • Proactively identify data quality issues, redundancies, or inefficiencies, and lead remediation efforts to maintain data integrity.

Data Hygiene & Validation:

  • Implement automated data profiling and testing suites to catch schema drift, enforce data hygiene, and handle missing or incomplete values before data is loaded. Metric Standardization:
  • Partner with clinical and analytics teams to standardize client metric definitions, ensuring data from different health systems is mapped into one consistent format. Schema Flexibility:
  • Design flexible ingestion pipelines capable of handling raw semi-structured data (like JSON) and new metric additions without breaking existing downstream models

What we're looking for:

  • Experience: 3–5 years in Analytics Engineering or Data Engineering, ideally within a B2B SaaS or Customer Success environment.
  • Core Stack: Expert proficiency in SQL and dbt. Demonstrated experience modeling complex, semi-structured data (JSON/FHIR) into clean analytical tables in BigQuery (or Snowflake).
  • Data Pipeline Management: Hands-on experience with ELT tools (Fivetran, Airbyte) and orchestration (Airflow, dbt Cloud). Ability to manage data flow from raw ingestion to the final BI layer.
  • CRM & Systems: Working knowledge of Salesforce data schemas (Objects, Leads, Opportunities). Experience with Reverse ETL (Hightouch/Census) to sync data back to business tools is a strong plus.
  • BI & Quality: Familiarity with Tableau (or Looker) to optimize data sources for performance. Strong understanding of data governance, testing (dbt tests), and version control (Git).
  • Mindset: Proactive problem solver who focuses on maintainable, scalable architecture over one-off scripts. Excellent attention to detail. Deep, practical expertise in using Python to create bespoke API integrations, automate workflows, and develop operational data processes, exceeding the capabilities of standard connectors.

Tell me more about Suki

  • On a roll: Named by Fast Company as one of the most innovative companies, named Google’s Partner of the Year for AI/ML, named by Forbes as one of the top 50 companies in AI .
  • Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems.
  • Great investors: We’re backed by Venrock, First Round Capital, Flare Capital, March Capital, Hedosophia and others. With our $165M raised so far, we have the resources to scale.
  • Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it.
  • Great customers: Our solutions are used in health systems and clinics across the country, supporting clinicians across dozens of specialties. Check out what one of our users says about how Suki has helped his practice.
  • Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better.

Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.

 

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