Senior Data Engineer

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🔥 0 minutes ago

🏄 California, New York, +1 more states – Remote

🏄 California – Remote 🗽 New York – Remote ☕ Washington – Remote

💵 $150k - $220k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Verantos

WebsiteLinkedInAll Job Openings

51 - 200 employees

⚕️ Healthcare Insurance

💊 Pharmaceuticals

🔬 Science

💰 Grant on 2021-06

Healthcare Insurance • Pharmaceuticals • Science

Verantos is a company that provides high-quality real-world data (RWD) and real-world evidence (RWE) solutions for the life sciences industry. Their platform is designed to accelerate clinical development and support market access, medical affairs, pharmacovigilance, and regulatory initiatives using high-validity evidence. Verantos focuses on delivering data with unrivaled richness and reliability, enabling decision-makers in healthcare to understand patient behaviors and predict health outcomes. The company offers products such as the Pragmatic Registry, which collects clinically rich data from patient records to aid in regulatory and reimbursement approvals. Verantos aims to meet increasing demands in the life sciences sector by providing credible and trustworthy evidence at scale.

📋 Description

• Lead the design and evolution of the data platform architecture, establishing patterns and standards the team builds on. • Build and operate production-grade data pipelines that ingest and transform high-variance, real-world clinical data reliably and at scale. • Design for automation from the start: pipelines that detect problems, recover gracefully, and surface issues without requiring manual intervention to run. • Contribute to quarterly data product releases, working closely with product, clinical, customer success teams to meet commitments. • Build data quality tests that reflect the evolving needs of our downstream consumers. • Mentor and elevate other data engineers through code review, architecture decisions, and shared standards. • Actively use and advocate for AI tools that improve the team's development velocity and code quality.

🎯 Requirements

• 8+ years in data engineering, with experience at a technical lead level. • Production experience with Snowflake and dbt as primary data platform tools. • Strong Python skills for building and maintaining data pipelines. • Has built resilient pipelines on irregular, high-variance data sources and knows what it takes to keep them running without babysitting. • Thinks in systems: designs for observability, failure recovery, and automation. • Can engage meaningfully with the business and domain context around the data, not just the engineering. • Uses AI tools actively in their own work and is curious about applying them within the pipeline, particularly for data quality monitoring and anomaly detection at scale. • Communicates clearly and works well across engineering, product, and clinical stakeholders.