4 days ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Design, maintain, and optimize BigQuery data architecture, standardized tables, and semantic models for Customer Success analytics and business intelligence.
- Build and manage ETL/ELT and Reverse ETL pipelines connecting BigQuery, Salesforce, Gainsight, and external customer signals.
- Set up and manage GCP infrastructure, including Cloud Storage buckets, triggers, and scheduled workflows for ingestion and transformation.
- Own data ingestion from raw sources through the BI layer using ELT tools, configuration-based connectors, and orchestration platforms.
- Implement automated data profiling, dbt testing, anomaly detection, schema drift handling, freshness alerts, and data quality remediation.
- Optimize analytical models and data sources for high-performance Tableau or other BI dashboards.
- Standardize client metrics and map data from different health systems into consistent formats.
- Collaborate with Customer Success, Product, Finance, Sales, clinical, and analytics teams on data definitions, governance, access, and quality.
- Use Python to build bespoke API integrations, automate workflows, and develop operational data processes.
- Document data architecture, pipelines, automation workflows, and governance standards.
Requirements
- 3–5 years of experience in Analytics Engineering or Data Engineering, ideally in a B2B SaaS or Customer Success environment.
- Expert proficiency in SQL and dbt, with experience modeling complex semi-structured JSON or FHIR data into analytical tables.
- Hands-on experience with ELT tools such as Fivetran or Airbyte and orchestration using Airflow or dbt Cloud.
- Experience managing data flow from raw ingestion through the final BI layer.
- Working knowledge of Salesforce data schemas, including Objects, Leads, and Opportunities.
- Experience with Reverse ETL tools such as Hightouch or Census is strongly preferred.
- Familiarity with Tableau or Looker and experience optimizing data sources for BI performance.
- Strong understanding of data governance, automated testing, version control, and dbt tests.
- Deep practical expertise using Python for API integrations, workflow automation, and operational data processes.
- Strong attention to detail and a focus on maintainable, scalable architecture rather than one-off scripts.
Benefits
- High-visibility founding role with ownership of Suki’s semantic layer and Customer Success data infrastructure.
- Opportunity to make an impact on healthcare technology and reduce clinicians’ administrative burden.
- Join a team of technologists, clinicians, and healthcare industry experts backed by experienced investors and $165M raised.
- Equal Opportunity Employer committed to inclusion and belonging.
Tech Stack
Categories
Data Engineering
About Suki
Suki builds AI-powered voice tools for healthcare, including Suki Assistant for ambient clinical documentation and coding support and the Suki Platform for partners to embed speech and NLP. It sells software to health systems and clinics to reduce administrative work and improve note quality, integrating with electronic health records. Founded in 2017 and based in Redwood City, California, Suki is privately held and raised a Series D round in 2024.