Lead Data Solutions Engineer

Key Skills

Aartificial intelligence, Amazon Athena, Amazon RedShift, Amazon Simple Storage Service (S3), Continuous Integration & Continuous Delivery - CI/CD, Data Engineering, Data science techniques, DynamoDB, Elasticsearch, ETL frameworks, Leadership Skill, Machine learning techniques, Python Programming, R Programming, Scala Programming, SQL

Job Description

Our dynamic team of scientists and engineers not only discover new therapies and technologies, but also lead an aspirational charge to pioneer scientific breakthroughs that have the potential to prevent and ultimately cure chronic disease. 

Apply today and join us for a life-changing career!

The Position 

As our new Lead Data Solutions Engineer, you will contribute to designing, implementing, and deploying analytics products based on latest advances in AI/ML, to create novel, world-leading solutions with broad applications within healthcare technology.

You will bring elements of appropriate data architecture and engineering, together with infrastructure teams, to translate data science solutions into highly available, scalable, reusable, consistent, secure, and enterprise-enabled systems and platforms, specifically for applications of AI/ML. 

Moreover, collaboratively with Data Scientists and ML Engineers, you will contribute to the development, validation, and deployment of AI/ML algorithms and models, and work closely with other engineers to build AI/ML-fueled products. 

As a senior individual contributor, you will provide technical leadership and mentoring to team members and involve in supporting their career growth. 

Responsibilities 

• Collaborate with various data science, ML, AI, imaging, bioinformatics, real-world evidence, and other research teams to build modern data-driven enterprise-ready solutions. 
• Interface with business partners to lead architecture and development of enterprise cloud-based data solutions and pipelines that feed into data science solutions. 
• Work with the data engineering, data science, and data ownership teams to collect relevant data elements and implement data pipelines (data acquisition, preparation, cleaning, and consolidation) as an integral part of data science activity. 

• Work closely with various stakeholders to provide end-to-end support in data ETL and consumption. 
• Transform and grow data science prototypes into scalable, reliable, secure, and maintainable, AI-powered software products based on distributed architectures. 

You will work and collaborate in cross-functional teams with IT, machine learning engineers, and data scientists in application areas ranging from real-world data and omics to computer vision and natural language processing. The workplace is Soeborg Denmark, but flexible or remote work arrangements can be discussed. 

Qualifications 

You have either a MSc degree with 5+ years of relevant experience or a PhD degree with 3+ years of relevant experience. Degrees within computer science, mathematics, engineering, physics, statistics, or a related quantitative discipline are preferred. 

Relevant experience includes: 

• Building and operationalizing complex data solutions, correcting problems, applying transformations, and recommending data cleansing/quality solutions. 

• Ensuring the quality of the data in coordination with data analysts, data scientists, and business partners (peer validation). ETL practices such profiling, cleansing, transforming, developing and documenting data structures, schemas, and dictionaries. 
• SQL, DynamoDB, RedShift, EFS, EMR, EBS, ElastiCache and other relational/non-relational database technologies/concepts. 
• AWS data-related services such as Storage Gateway, CloudWatch, Glue, Athena, S3, Lambda, Data Pipeline, Data Migration, Step functions. 
• Cloud & software engineering: microservices, Kubernetes, GPU & high-performance computing. Versioning (git), CI/CD, DevSecOps, observability, agile development. 
• Working knowledge of programming languages: Python (mandatory), R, Scala. 

• Thought leadership within the field of data engineering and technical leadership of more junior team members in engineering teams. 

As a person you ensure a healthy, engaging, and inclusive work environment. You are capable of building trust and relationships across functions and cultures. You demonstrate agility and adapt quickly to changes.