Senior Data Engineer

🕒 Abril 22

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Perform

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2005

🤝 B2B

🏢 Corporativo

B2B • Enterprise

A Perform é uma empresa de serviços de engenharia de software nearshore, fundada em 2005, que oferece equipes de desenvolvimento remoto e staff técnico para ajudar empresas a escalarem suas aplicações e capacidade de engenharia. A empresa recruta e coloca engenheiros nos Estados Unidos e América Latina, oferecendo cargos como Desenvolvedores Full Stack e Engenheiros de Dados e gerenciando folha de pagamento, benefícios e logística operacional para o staff remoto. A Perform foca em parcerias de longo prazo e em ajudar empresas a expandirem seus produtos e equipes por meio de talentos de engenharia distribuídos e remotos.

Descrição

• Own the Data Platform • Design, build, and operate MDVIP’s data platform on Azure Databricks—ingestion, transformation, storage, and serving layers that power analytics, AI models, and operational reporting. • Build and maintain data pipelines across MDVIP’s ecosystem: Salesforce, SQL Server, Snowflake, third-party sources, and the new cloud-native payments platform. • Engineer for quality and trust—validation checks, anomaly detection, lineage tracking, and documentation that ensure every downstream consumer can rely on the data. • Write clean, version-controlled, production-grade code. • Think like a software engineer building a product, not a script runner maintaining jobs. • Go Deep Into the Business Domain • Partner directly with business stakeholders across physician growth, member services, finance, and operations to understand how data drives decisions—then build for those decisions, not for abstract requirements. • Act as a technical product owner for your domain areas: own the backlog, prioritize based on business impact, and ship iteratively without waiting for a PM to sequence your work. • Translate ambiguous business questions into data models, feature tables, and curated datasets that analysts and data scientists can build on immediately. • Close the loop—follow your data through to the dashboard, the model, or the operational workflow and validate that it’s actually driving the outcome. • Drive AI-First Engineering Practices • Use Claude Code and agentic development as your primary workflow—AI-driven pipeline generation, automated testing, rapid prototyping—to ship at a pace that would be impossible with traditional approaches. • Build data infrastructure that is AI-ready: well-documented, semantically clear, and structured so that AI tools and agents can reason over it effectively. • Scout, evaluate, and adopt emerging AI tools and platforms that make the data team faster—separating real value from hype with hands-on testing. Share what you learn. Document patterns, run demos, and help the broader team adopt AI-first workflows with confidence.

🎯 Requisitos

• BS in Computer Science, Data Science, or related field; 6+ years in data engineering or a hybrid data engineering/analytics role. • Deep hands-on experience with Azure Databricks—notebooks, Delta Lake, Unity Catalog, and production-scale pipelines. • Strong Python and SQL; experience with PySpark and distributed data processing. • Built and operated data pipelines that serve analytics, ML models, and operational systems—not just batch ETL jobs. • Worked directly with business stakeholders to define requirements, shape data products, and deliver measurable outcomes. • Active, daily use of AI coding tools (Claude Code, Copilot, or similar) as a force multiplier. • Strong communication skills with a track record of presenting technical work to non-technical audiences.

🏖️ Benefícios

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development