Senior Data Engineer

Work on data‑driven strategies to apply AI and ML to novel drug discovery, at the forefront of biotech innovation.

Salary: $140,000 – $180,000 per year

You'll play a central role in shaping the company’s data platform by contributing to ingestion frameworks, orchestration patterns (using Dagster
, Prefect or Airflow
), and dbt‑based modeling strategies. This high‑impact role is 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

• Position:
  Senior Data Engineer
• Industry: Scientific/Biotech
• Location:
  
  Remote (NYC/Boston optional), U.S.
• Experience:
  
  5+ years in data engineering or related fields
• Tools:
  Python, SQL, dbt, Snowflake, and orchestration tools such as Dagster, Prefect, or Airflow
• Responsibilities include design, construction, installation, testing, and maintenance of highly scalable data management systems; building high‑performance pipelines and predictive models; and collaborating with data architects and stakeholders.

• 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.

• 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.
• Enjoy partnering with stakeholders and ensuring clean, discoverable data.

• Experience working in pharma, healthcare, or regulated data environments.
• Experience working with unstructured data and AI data engineering (OCR, NER, vector databases, graph databases).

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories.

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