Senior Data Engineer

🕒 Maio 21

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9amHealth

SiteLinkedInTodas as Vagas

11 - 50 funcionários

💰 $16.000.000 Series A em 2022-04

9amHealth é cuidado cardiometabólico completo — uma abordagem inovadora e abrangente para prevenir e tratar diabetes, obesidade, colesterol alto e hipertensão. Parcerizamos com empresas que buscam fornecer benefícios de saúde eficazes para seus membros, ao mesmo tempo em que reduzem os custos gerais de saúde.

Descrição

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows in Python using AWS Glue, Apache Spark, Airflow, or equivalent orchestration tools. • Write production-grade Python code for DWH logic, reporting jobs, data transformations, and internal tooling, following software engineering best practices (testing, code review, CI/CD). • Develop and optimize analytical data models (dimensional, OBT, or hybrid) that serve self-service BI and advanced analytics use cases. • Build and maintain dashboards, explores, and semantic layers in Looker and/or Tableau; serve as the analytics infrastructure owner ensuring data quality and governance. • Contribute backend application code in Java (Spring Boot) or Python to support data-intensive features, API integrations, and internal services. • Champion modern AI coding practices across the data team, leveraging tools like GitHub Copilot, Claude, Cursor, or similar AI-assisted development environments to accelerate delivery and code quality. • Author and maintain comprehensive SQL assets (stored procedures, views, complex queries) across Redshift, Aurora/MySQL, and Athena. • Operate and optimize AWS data infrastructure including Glue, S3, Redshift, CloudFormation, CloudWatch, IAM, and Athena. • Collaborate closely with clinical operations, product, finance, and engineering teams to translate business questions into reliable, well-documented data products. • Implement data quality frameworks, monitoring, alerting, and incident response processes for the data platform. • Contribute to the architecture and data strategy for AI/ML features, including data prep, feature engineering, and model monitoring. • Mentor the existing data analyst and data engineer; help establish team standards, code review practices, and documentation norms.

🎯 Requisitos

• 10+ years of professional experience in data engineering, analytics engineering, or a hybrid data/backend software engineering role. • Strong software engineering background: this role requires someone who can write, test, debug, and ship production code, not just query data. • Expert-level Python: deep experience building production data pipelines, ETL logic, and reporting systems in Python. • Expert-level SQL: window functions, CTEs, recursive queries, query optimization, and performance tuning at scale. • Hands-on experience with AWS data services, specifically Glue, S3, Redshift, Athena, CloudFormation, CloudWatch, and IAM. • Experience with MySQL/Aurora in a production environment. • Hands-on experience building and operating data pipelines with AWS Glue, Spark, dbt, Airflow, or comparable frameworks. • Deep experience with at least one modern BI platform. Looker (LookML) strongly preferred; Tableau also valued. Should include semantic modeling, dashboard design, and self-service enablement. • Solid understanding of data modeling techniques: star/snowflake schemas, slowly changing dimensions, event-based models. • Familiarity with AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, Cody) and a demonstrated interest in integrating AI into engineering workflows. • Proficiency in Java (Spring Boot, Maven/Gradle) with experience shipping backend services or data-intensive applications to production. • AWS certifications (e.g., Solutions Architect, Data Analytics Specialty, or Database Specialty). • Experience in health tech, digital health, or regulated industries (HIPAA familiarity is a plus). • Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar). • Background in building or contributing to AI/ML features: feature stores, training pipelines, model serving, or RAG architectures. • Comfort with infrastructure-as-code (Terraform, CloudFormation) and containerized deployments (Docker, ECS/EKS). • Prior experience in a startup or high-growth environment where you owned outcomes end to end. • Track record of improving developer experience and productivity through tooling, automation, or process improvements.

🏖️ Benefícios

• Health insurance • Dental insurance • Vision insurance • Flexible PTO • Work from home options • Professional development budget • Support continuing education