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Datavant

De-identification and linking health data SaaS

Senior Data Engineer

Data EngineeringUpdated on Nov 9
Full-time

About the Job

Requirements

  • At least 7 years of experience in software development or data engineering, including contributing to complex technical initiatives and collaborating across teams.
  • Experience using AI-assisted engineering tools to improve development workflows, code quality, operational efficiency, and scalability.
  • Strong experience with modern data modelling, transformation practices, and scalable architecture patterns across analytical and operational domains.
  • Experience designing and operating data pipelines and orchestration frameworks using technologies such as dbt, Apache Airflow, Python, and cloud-native platforms.
  • Experience building and operating cloud-based data platforms in AWS, Azure, or GCP, including Infrastructure-as-Code practices using Terraform or similar tools.
  • Experience supporting platform reliability through observability, monitoring, operational excellence, performance optimisation, and cost management.
  • Familiarity with CI/CD pipelines, automated testing strategies, and modern software engineering practices for reliable data platforms.
  • Ability to partner effectively across engineering, analytics, product, and operations teams.
  • Ability to balance competing priorities, navigate ambiguity, and deliver impactful solutions.

Responsibilities

  • Design and evolve scalable data platform infrastructure, orchestration frameworks, and data models that support reporting, analytics, and operational systems.
  • Partner across Product, Engineering, Analytics, and Operations to translate business needs into scalable data solutions and platform capabilities.
  • Build and maintain reliable, observable, and reusable data workflows using Python, SQL, dbt, Airflow, Terraform, and cloud-native technologies.
  • Lead technical discussions and architecture decisions, balancing scalability, reliability, maintainability, cost, and delivery speed.
  • Mentor engineers and help establish best practices for data engineering, observability, Infrastructure-as-Code, and operational excellence.
  • Drive improvements in testing, monitoring, reliability, security, and cost optimisation across the platform.
  • Review code, infrastructure, and architecture to support high standards of quality, maintainability, and performance.

Desired Qualifications

  • Prior experience in healthcare or another highly regulated industry such as finance, insurance, or life sciences.
  • Experience administering and optimising Snowflake or similar cloud data warehouse platforms, including security and access management, performance tuning, workload management, cost optimisation, governance, and operational reliability at scale.
  • Hands-on experience with modern data stack technologies such as dbt, Fivetran, Airflow, Kafka, Spark, Databricks, or streaming/event-driven architectures.
  • Strong understanding of data governance, privacy, lineage, and compliance frameworks such as HIPAA, HITRUST, SOC 2, or GDPR.
  • Background as a Database Administrator, Data Analyst, Analytics Engineer, or similar data-focused role.
  • Experience building self-service data platforms, reusable developer tooling, or internal platform capabilities that improve engineering productivity.
  • Experience supporting multi-cloud or hybrid-cloud infrastructure and networking patterns across AWS and/or Azure.

About the Company

Datavant

De-identification and linking health data SaaS

Datavant provides software to securely share health data by removing personal identifiers and linking records from multiple sources. Its SaaS platform de-identifies datasets and connects data across hospitals, research centers, pharma, and public health groups for cohesive analysis. It differentiates itself by combining privacy-preserving de-identification with cross-source data linkage in the health sector, supporting interoperability while protecting privacy. Its goal is to enable secure, privacy-friendly exchange of health information to advance research, patient care, and public health.

Company size
5,001-10,000
Company stage
Series B
Total funding
$80.5M
Headquarters
San Francisco, CA
Founded
2017

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