Senior / Lead Data Engineer - Life Sciences

Evolution USA; Boston (MA); Presencial; USD 120 000 - 190 000; Tempo integral

Resumo da oferta

Evolution USA is seeking experienced Data Engineers to own complex, production-scale data solutions in a fast-moving biotech environment.

You will design and implement scalable data pipelines, models, and lakehouse architectures, working with Python, SQL and cloud platforms across AWS/Azure/GCP. You’ll lead technical discussions, mentor peers, and collaborate with stakeholders to turn ambiguous requirements into robust production solutions.

Qualificações

• Extensive experience in data engineering or data-intensive software engineering.
• Proficient in Python and SQL.
• Hands-on with Databricks and Snowflake.
• Strong understanding of data pipelines, modeling and lakehouse architectures.

Responsabilidades

• Design and build scalable data pipelines and processing frameworks.
• Develop robust data models for complex datasets.
• Design lakehouse and medallion-style architectures.
• Build production-grade solutions with Python and SQL.
• Work with Databricks or Snowflake.
• Make architectural data ingestion, transformation decisions.
• Lead projects from requirements through production.
• Improve engineering quality via testing and reusable components.
• Mentor other engineers and lead technical discussions.
• Collaborate with stakeholders to translate ambiguous requirements.

Conhecimentos

Python

SQL

Databricks

Snowflake

Data pipelines

Data modeling

Cloud AWS

Leadership

Mentoring

Descrição da oferta de emprego

We're working with a growing BioTech company that is looking for a couple of experienced Data Engineers to take ownership of complex, production-scale data solutions.

These are hands-on engineering roles for someone who enjoys taking difficult, loosely defined data problems and turning them into robust, scalable systems.

You'll have significant technical autonomy, working across data architecture, modelling, processing and pipeline development while helping guide other engineers and influencing how the wider data platform evolves.

The priority is finding excellent engineers with strong fundamentals, intellectual curiosity, and the ability to take ownership in a fast-moving environment.

What you'll be doing

• Designing and building scalable data pipelines and processing frameworks
• Developing robust data models for complex, varied datasets
• Designing modern lakehouse and medallion-style data architectures
• Building production-grade solutions using Python and SQL
• Working extensively with Databricks or Snowflake
• Making architectural decisions around how data is ingested, transformed, modelled and consumed
• Taking technical projects from initial requirements through design, implementation and production
• Improving engineering quality through testing, reusable components and strong development practices
• Leading technical discussions and helping mentor other engineers
• Working with multiple stakeholders to turn ambiguous requirements into practical solutions
• Identifying bottlenecks and proactively driving projects towards successful delivery

What we're looking for

• Strong professional experience in data engineering or data-intensive software engineering
• Excellent Python and SQL
• Deep understanding of data processing, data modelling and data pipeline architecture
• Commercial experience with Databricks and/or Snowflake
• Strong understanding of modern lakehouse / medallion architecture
• Cloud experience across AWS, Azure or GCP
• Strong software engineering fundamentals, including testing and maintainable code
• Experience taking technical ownership of complex projects
• Comfortable working in an environment where requirements aren't always perfectly defined
• Someone naturally curious who enjoys learning new domains and solving unfamiliar problems

Why apply!

You'll have the opportunity to work on unusually complex datasets and engineering problems while having real influence over architecture and delivery.

This isn't a role where you'll simply maintain existing ETL jobs. You'll be expected to understand the underlying data problem, determine the right architecture, build the solution and take responsibility for getting it successfully into production.

It's particularly well suited to an engineer who likes ownership, technical variety and solving problems without being handed a detailed playbook.