Job Description
As a Analytics Engineer, you will be part of the HHIAD Commercial Data Solutions team, providing technical/data expertise development of analytical data solutions to enable data science & analytics use cases. In this role, you will create and maintain data assets/domains used in the commercial/marketing analytics space – to develop best-in-class data pipelines and products, working closely with data product owners to translate data requirements and user stories into development activities throughout all phases of design, planning, execution, testing, deployment and delivery.
Your specific responsibilities will include:
- Design and implementation of last-mile data products using the most up-to-date technologies and software/data/DevOps engineering practices
- Enable data science & analytics teams to drive data modeling and feature engineering activities aligned with business questions and utilizing datasets in an optimal way
- Develop deep data domain expertise and business acumen to ensure that all specificifities and pitfalls of data sources are accounted for
- Build data products based on automated data models, aligned with use case requirements, and advise data scientists, analysts and visualization developers on how to use these data models
- Develop analytical data products for reusability, governance and compliance by design
- Design and Implement semantic layer for analytics data solutions
- Support data stewards and other engineers in maintaining data catalogs, data quality measures and governance frameworks
Education:
- B.S., M.S. or PhD in Engineering, Pharmaceuticals, Healthcare, Computer Science, Data Science, Business, or related field
Required experience:
- 5 – 6 years of relevant work experience in the pharmaceutical/life sciences industry, with demonstrated hands-on experience in analyzing, modeling and extracting insights from commercial/marketing analytics datasets (specifically, real-world datasets)
- High proficiency in SQL, Python and Cloud systems
- Experience with Data quality management techniques
- Experience creating / adopting data models to meet requirements from Data Science / Visualization stakeholders
- Experience with data science/machine learning use cases, including feature engineering
- Experience with cloud-based (AWS / GCP / Azure) data management platforms and typical storage/compute services (Snowflake, Redshift, etc.)
- Experience with modern data stack tools such as dbt, Starburst, ThoughtSpot, Databricks and low-code tools (e.g. Dataiku)
- Excellent interpersonal and communication skills, with the ability to quickly establish productive working relationships with a variety of stakeholders
- Experience in analytics use cases of pharmaceutical products and vaccines
Preferred experience:
- Experience in analytics use cases focused on informing marketing strategies and commercial execution of pharmaceutical products and vaccines
- Experience with Agile ways of working, leading or working as part of scrum teams
- Certifications in AWS and/or modern data technologies
- Knowledge of the commercial/marketing analytics data landscape and key data sources/vendors
- Experience in building data models for data science andvisualization/reportingproducts, in collaboration with data scientists, report developers and business stakeholders
- Experience with data visualization technologies (e.g, PowerBI)
What we look for …
Current Contingent Workers apply
*A job posting is effective until 11:59:59PM on the dayBEFOREthe listed job posting end date. Please ensure you apply to a job posting no later than the dayBEFOREthe job posting end date.
Job Posting End Date:08/07/2024
A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.