Highly Skilled Data Engineer for Scalable Data Solutions

2 weeks ago

London, Greater London, United Kingdom Causaly Full time
About Causaly

Causaly accelerates how humans acquire knowledge and develop insights in Biomedicine. Our production-grade generative AI platform enables thousands of scientists to discover evidence from millions of academic publications, clinical trials, regulatory documents, patents, and other data sources.

We work with some of the world's largest biopharma companies and institutions on use cases spanning Drug Discovery, Safety, and Competitive Intelligence. You can read more about how we accelerate knowledge acquisition and improve decision-making in our blog posts here: Blog - Causaly

We are backed by top VCs including ICONIQ, Index Ventures, Pentech, and Marathon.

Job Description

You will join our Data & Semantic Technologies team, responsible for delivering the scalable and highly flexible data fabric that is the foundation of Causaly's product suite. This team is enabling and empowering new product developments as well as innovations in AI to create true business value. You will be unleashing the value of data for our customers through building and operating automated data pipelines, feeding our constantly growing data warehouse and knowledge graph, evolving our data architectures, etc.

This role involves gathering and understanding data based on business requirements, regularly importing and transforming big data from various formats into data stores like BigQuery and Neo4j, processing data further using SQL and/or Python, working with other engineers on highly performant data pipelines, exporting data in well-defined target formats, ensuring and validating data output and quality, producing corresponding reports and dashboards, managing and improving legacy data pipelines in the cloud, innovating on our data warehouse architecture and usage, working directly with technical, product, and business stakeholders, mentoring junior members, shaping our technology strategy, and collaborating with the DevOps team to help manage our infrastructure.

Requirements
  • Significant industry experience working with SQL, automation, ETL, Linux
  • Proven database skills and experience with traditional RDBMS like MySQL as well as modern systems like BigQuery
  • Experience with data versioning, data-backup, and data-recovery strategies
  • Solid understanding of modern software-development practices (testing, version control, documentation, etc.) and hands-on coding experience in Python
  • Experience with cloud computing providers like GCP/AWS
  • Strong engineering background enabling rapid progression from ideation to proof-of-concept
  • A product and user-centric mindset
  • Excellent problem-solving, ownership, organizational skills, with high attention to detail and quality
Benefits
  • Estimated salary range $120,000-$160,000 per annum
  • Competitive compensation package
  • Private medical insurance (underwritten on a medical health disregarded basis)
  • Life insurance (4 x salary)
  • Individual training/development budget through Learnerbly
  • Individual wellbeing budget through Juno
  • 25 days holiday plus public holidays and 1 day birthday leave per year
  • Hybrid working (home + office)
  • Potential to have real impact and accelerated career growth as an early member of a multinational team that's building a transformative knowledge product
Why Work at Causaly?

Diversity, Equity, Inclusion. They are more than words at Causaly. It's how we work together. It's how we build teams. It's how we grow leaders. It's what we nurture and celebrate. It's what helps us innovate. It's what helps us connect with the customers and communities we serve.

We are on a mission to accelerate scientific breakthroughs for ALL humankind, and we are proud to be an equal opportunity employer. We welcome applications from all backgrounds and fairly consider qualified candidates without regard to race, ethnic or national origin, gender, gender identity or expression, sexual orientation, disability, neurodiversity, genetics, age, religion or belief, marital/civil partnership status, domestic/family status, veteran status or any other difference.

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