Scientific Data Engineer - Boston, England, United Kingdom - Arrayo

    Arrayo
    Arrayo Boston, England, United Kingdom

    2 weeks ago

    Default job background
    Description

    Data Engineer

    We are seeking a skilled Data Engineer to join our cross-disciplinary team and contribute to the development of scalable, metadata-rich data products that adhere to FAIR principles.

    In this role, you will work closely with platform, scientific, and AI/ML teams to build and maintain curated datasets and robust data pipelines. These pipelines will support analytics, modeling, and deep learning within platforms such as AWS, Azure Databricks, and Domino Data Lab.

    Key Responsibilities:

    • Develop, deploy, and maintain scalable, cloud-native data pipelines for molecular modeling and related domains.
    • Operationalize architectural blueprints using modern orchestration frameworks and cloud services (AWS/Azure).
    • Partner with scientists, cheminformaticians, and data scientists to understand domain-specific requirements and deliver efficient, reusable data solutions.
    • Process and integrate molecular property datasets, embedding rich metadata to maximize downstream value for AI/ML applications.
    • Establish data quality, lineage, and governance standards in line with FAIR principles, ensuring reproducibility, traceability, and compliance.
    • Enable interactive dataset exploration through tools like Spotfire.
    • Shape schema design, enrich metadata, and develop APIs for reliable and flexible data access.
    • Optimize storage and compute performance across data lakes and warehouses (e.g., Delta Lake, Parquet, Redshift).
    • Document data contracts, pipeline logic, and operational best practices to ensure long-term sustainability and effective collaboration.

    Required Qualifications:

    • Demonstrated experience as a data engineer in biopharmaceutical or life sciences, particularly supporting drug discovery or translational research.
    • Hands-on work with molecular structure data, computed properties, simulation outputs, or imaging datasets.
    • Proficiency in Python (including Pandas or PySpark) and SQL, with exposure to ETL/orchestration tools such as Airflow or dbt.
    • Strong knowledge of cloud-native services on AWS (e.g., S3, Glue, Lambda, Athena) and Azure (Data Factory, Data Lake).
    • Track record of collaborating with scientific teams and translating research needs into scalable data solutions.

    Preferred Qualifications:

    • Experience with cheminformatics libraries (e.g., RDKit, Open Babel, CDK).
    • Familiarity with scientific data standards, ontologies, and best practices for metadata capture.
    • Understanding of data science workflows in computational chemistry, bioinformatics, or AI/ML-driven research.
    • Orchestration & ETL: Apache Airflow, Prefect
    • Scientific Libraries (Preferred): RDKit, Open Babel, CDK

    Seniority level

    • Mid-Senior level

    Employment type

    • Full-time

    Job function

    • Engineering, Research, and Information Technology
    • Biotechnology Research, Pharmaceutical Manufacturing, and IT Services and IT Consulting
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