AI-Driven Scientific Data Platform Engineer

tropicbioscience; Norwich; Hybrid; GBP 55,000 - 85,000; Full time

Benefits offered by this job

Private Health Care

Medical Cash Plan

25 days annual leave

Life Assurance

Job summary

Tropic is seeking its first dedicated data engineer to define and build a connected data foundation for a high-value scientific estate. You will shape architecture that links scientific and operational data, enabling AI and analytics across science, commercial, pipeline and supply.

In your first year you will launch the first connected scientific data layer and operationalise shared architecture aligning genome-editing designs with experimental outcomes to drive smarter design decisions and

Qualifications

• Around five years' experience in data engineering or a related data-platform role.
• Strong hands-on experience with Python and SQL.
• Experience designing data models and data architectures across multiple systems and building and operating production-quality ETL/ELT pipelines and automated data workflows.
• Experience integrating heterogeneous data sources, databases and APIs.

Responsibilities

• Design and build scalable data architecture, models, pipelines and integrations across scientific and business systems.
• Establish consistent approaches to identifiers, metadata, data quality, lineage and traceability.
• Create reusable data foundations that support bioinformatics, analytics, machine learning and AI.
• Evaluate technical options and help establish data-engineering standards and best practices.
• Work closely with scientists, Bioinformatics and IT to translate complex questions into practical data solutions.

Skills

Python

SQL

Data modeling

ETL/ELT pipelines

Airflow

Dagster

dbt

Data quality

Metadata & lineage

Communication

Tools

Airflow

Dagster

dbt

Job description

Tropic is seeking its first dedicated data engineer to define and build a connected data foundation for a high-value scientific estate. You will shape architecture that links scientific and operational data, enabling AI and analytics across science, commercial, pipeline and supply.

In your first year you will launch the first connected scientific data layer and operationalise shared architecture aligning genome-editing designs with experimental outcomes to drive smarter design decisions and