Jr. Analytics Engineer - Data Solutions

We are seeking a talented, motivated and self-driven professional to join the HH Digital, Data & Analytics (HHDDA) organization and play an active role in Human Health transformation journey to become the premier Data First commercial biopharma organization.

As a Lead Analytics Engineer, you will be part of the HHDDA Commercial Data Solutions team, providing technical/data expertise development of analytical data products 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 product 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 / Dev

Ops 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 domain expertise and business acumen to ensure that all specificalities 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

• Align with organization strategy and implement semantic layer for analytics data products

• Support data stewards and other engineers in maintaining data catalogs, data quality measures and governance frameworks

Education:

• B.Tech / B.S., M.Tech / M.S. or PhD in Engineering, Computer Science, Engineering, Pharmaceuticals, Healthcare, Data Science, Business, or related field.

Required experience:

• 8+ 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 AWS

• Experience creating / adopting data models to meet requirements from Marketing, Data Science, Visualization stakeholders

• Experience with including feature engineering

• Experience with cloud-based (AWS / GCP / Azure) data management platforms and typical storage/compute services (Databricks, Snowflake, Redshift, etc.)

• Experience with modern data stack tools such as Matillion, Starburst, Thought

Spot 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

• Experience in market analytics and related use cases

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 and visualization/reporting products, in collaboration with data scientists, report developers and business stakeholders

• Experience with data visualization technologies (e.g, PowerBI)