NHS Human Services, Inc.

At Genmab, we're committed to building extra[not]ordinary futures together, by developing antibody products and pioneering, knock-your-socks-off therapies that change the lives of patients and the future of cancer treatment and serious diseases. From our people who are caring, candid, and impact-driven to our business, which is innovative and rooted in science, we believe that being proudly unique, determined to be our best, and authentic is essential to fulfilling our purpose.

The Role

The successful candidate will contribute to the mission of the global data engineering function and be responsible for many aspects of data including creation of data -as-a- product, architecture, access, classification, standards, integration, and pipelines. Although your role will involve a diverse set of data-related responsibilities, y our key focus will be on the enablement of data for the Commercial functions, including Data Science, Insights and Analytics, Digital Marketing, Medical Affairs, and across different markets such as US, Japan, and Global. You will have a balance of subject matter expertise in Commercial analytics as they apply to a biotechnology company and technical expertise for hands-on implementation . You will be expected to create workflows to standardize and automate data, connect systems, enable tracking of data, implement triggers and data cataloging. With your experience in the commercial pharma domain, you will possess knowledge of diverse data ecosystems such as p atient, EMR/EHR, internal CRM data like Veeva, digital channel datasets, and mor e. Your ultimate goal will be to place data at the fingertips of stakeholders and enable science to go faster. You will join an enthusiastic, agile, fast-paced and explorative global data engineering team.

This is a hybrid role that requires being onsite 60% of the time in Princeton, NJ.

Responsibilities

Design, implement and manage ETL data pipelines that ingest vast amounts of scientific data from public, internal and partner sources into various repositories on a c loud platform (AWS)

Enhance end-to-end workflows with automation that rapidly accelerate data flow with pipeline management tools such as Step Functions, Airflow, or Databricks Workflows

Implement and maintain bespoke databases for p rocessed commercial and scientific data

Innovate and advise on the latest technologies and standard methodologies in Data Engineering and Data Management, and be able to identify software solutions that can address hurdles in data enablement

Manage relationships and project coordination with external parties such as Contract Research Organization s (CRO) and vendor consultants / contractors

Define and contribute to data engineering practices for the group, establishing shareable templates and frameworks, determining best usage of specific cloud services and tools, and working with vendors to provision cutting edge tools and technologies

Collaborate with stakeholders to determine best-suited data enablement methods to optimize the interpretation of the data , including creat ing presentations and lead ing tutorials on data usage as appropriate

Apply value-balanced approaches to the development of the data ecosystem and pipeline initiatives

Proactively communicate data ecosystem and pipeline value propositions to partnering collaborators , specifically around data strategy and management practices


Requirements

BS/MS in Computer Science, Bioinformatics, or a related field with 5 years of software engineering experience or a PhD in Computer Science, Bioinformatics or a related field and 2 years of software engineering experience

Ex tensive skills and deep knowledge of ETL pipeline s , automation especially AWS data & workflow management tools such as Airflow, AWS Glue, Amazon Kinesis, AWS Step Functions, and CI/CD is a must

Excellent skills and deep knowledge in Python, Pythonic design and object-oriented programming is a must, including common Python libraries such as pandas. Experience with R a plus

Proficiency in SQL & Strong experience with any RDMS (e.g., SQL Server, MySQL, PostgreSQL or Oracle) is a must, a dvanced query optimization and database design a plus

Solid understanding of modern data architectures and their implementation offerings including Databricks' Delta Tables, Athena, Glue, Iceberg, and their applications to Lakehouse and medallion architecture

Experience with Snowflake or similar MPP cloud data warehousing solution along with knowledge of data warehousing concepts and best practices is desired

Familiarity with notebook-based IDEs for development such as Databricks (preferred), Jupyter , Colab etc. is highly desirable

Solid understanding of the Commercial analytics landscape at a biotechnology company and experience disseminat ing domain-specific data strategies with stakeholders

Solid understanding and e xperience in working with commercial claims/EMR/EHR data sets like Komodo, Symphony, IQVIA, DRG, l ab data , specialty pharma datasets and digital data s ets like Veeva SFMC, Web, Social, CRM etc.

Proficiency with modern software development methodologies such as Agile, source control, project management and issue tracking with JIRA

Proficiency with container strategies using Docker, Fargate and ECR

Proficiency with AWS cloud computing services such as Lambda functions, ECS, Batch and Elastic Load Balancer and other compute frameworks such as Spark, EMR, and Databricks


For US based candidates, the proposed salary band for this position is as follows:

$95,625.00---$159,375.00

The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience, and...

Equal Opportunity Employer - minorities/females/veterans/individuals with disabilities/sexual orientation/gender identity