Lead Data Engineer, Cloud-First Biotech Platform

flagshippioneeringinc; Cambridge; On-site; GBP 90,000 - 120,000; Full time

Job summary

Flagship Pioneering invites applications for a Lead Data Engineer within its Scientific Cloud group in Cambridge. The role focuses on modernizing data infrastructure, building scalable pipelines, and establishing best practices across data platforms.

You will collaborate with cross-functional teams spanning I&O, Lab IT, and data science, driving innovation through robust, observable systems. You will mentor engineers, set coding and deployment standards, and apply AI-assisted approaches to

Qualifications

• 6+ years in data engineering, preferably life sciences or healthcare.
• Design and operate cloud-native AWS data architectures.
• Proficient in Python and SQL for pipelines and automation.
• Experience with Dagster, dbt, Spark, Iceberg, Lake Formation, Athena, Glue.
• Strong Git, CI/CD, CDK, Docker, ECS experience.
• Experience handling structured and unstructured data (CSV/JSON/Parquet).

Responsibilities

• Act as technical lead on complex data engineering projects across interdependent systems.
• Lead the implementation of data infrastructure, platforms, tools, and data products.
• Improve reliability of data storage solutions (lakehouses, marts, warehouses).
• Build data pipelines for data lakes, marts, and platforms.
• Set engineering standards for testing, docs, release management, and monitoring.
• Oversee platform observability, resilience, capacity, and performance.
• Diagnose failures and lead incident reviews to drive fixes.
• Collaborate with I&O, Lab IT, PI Tech, data science and bioinformatics.
• Mentor junior engineers and establish standards.
• Leverage generative AI tools to accelerate pipeline development.

Skills

Data engineering

Cloud architecture

Python

SQL

Leadership

Tools

Dagster

dbt

Spark

Iceberg

Lake Formation

Athena

Glue

Git

CDK

Docker

ECS

Job description

Flagship Pioneering invites applications for a Lead Data Engineer within its Scientific Cloud group in Cambridge. The role focuses on modernizing data infrastructure, building scalable pipelines, and establishing best practices across data platforms.

You will collaborate with cross-functional teams spanning I&O, Lab IT, and data science, driving innovation through robust, observable systems. You will mentor engineers, set coding and deployment standards, and apply AI-assisted approaches to