Senior Data Engineer

About Us

Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, this organization has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. The organization partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients.

Why Join Us?

You'll play a central role in shaping the company's data platform by contributing to ingestion frameworks, orchestration patterns (using Dagster or alternatives like Prefect or Airflow), and dbt-based modeling strategies. This is a high-impact role for an experienced engineer who loves building clean pipelines, understands metadata and observability, and enjoys making data discoverable and trustworthy for analytics, operations, and product use cases.

• Competitive salary and total compensation ranges based on experience
• Work on site in NYC or Boston, or up to 100% from home anywhere in the US.
• Comprehensive health, vision, and dental coverage for individuals and families

Job Details

We are seeking a passionate and talented Senior Data Engineer to join our dynamic team in the scientific industry. The ideal candidate will have a strong background in data engineering and a deep understanding of modern data processing technology stacks. The successful candidate will be responsible for the design, development, testing, and deployment of highly scalable data management systems. This role requires a deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. The individual in this role must be comfortable working in a fast-paced and dynamic environment with a high degree of autonomy.

Responsibilities

• Design, construct, install, test, and maintain highly scalable data management systems.
• Ensure systems meet business requirements and industry practices.
• Build high-performance algorithms, prototypes, predictive models, and proof of concepts.
• Research opportunities for data acquisition and new uses for existing data.
• Develop data set processes for data modeling, mining, and production.
• Integrate new data management technologies and software engineering tools into existing structures.
• Create custom software components and analytics applications.
• Install and update disaster recovery procedures.
• Collaborate with data architects, modelers, and IT team members on project goals.
• Employ a variety of languages and tools to marry systems together.
• Recommend ways to improve data reliability, efficiency, and quality.
• Use Dagster or equivalent for creating data pipelines and workflows.

Qualifications

• 5 years of experience in data engineering or related fields.
• Strong hands-on experience with Python, SQL, and dbt.
• Proficiency with orchestration tools like Dagster, Prefect, or Airflow.
• Experience building data ingestion pipelines from REST APIs, flat files, and cloud storage (e.g., S3).
• Familiarity with Snowflake and its ecosystem—warehouses, cost optimization, RBAC, data sharing.
• Clear understanding of metadata, observability, and testing for data pipelines.
• You enjoy partnering with stakeholders and understand the importance of clean, discoverable data.
• Bonus: experience working in pharma, healthcare, or regulated data environments.
• Bonus: experience working with unstructured data and AI Data Engineering (OCR, NER, vector databases, graph databases)