
Analytics Engineer
- Hyderabad, Telangana
- Permanent
- Full-time
- Hands-on development 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 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
- B.Tech / B.S., M.Tech / M.S. or PhD in Engineering, Computer Science, Engineering, Pharmaceuticals, Healthcare, Data Science, Business, or related field
- 5+ 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
- Good understanding and comprehension of the requirements provided by Data Product Owner and Lead Analytics Engineer
- 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, ThoughtSpot 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
- 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)
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.Employee Status: RegularRelocation:VISA Sponsorship:Travel Requirements:Flexible Work Arrangements: HybridShift:Valid Driving License:Hazardous Material(s):Required Skills: Business Intelligence (BI), Data Management, Data Modeling, Data Visualization, Measurement Analysis, Stakeholder Relationship Management, Waterfall ModelPreferred Skills:Job Posting End Date: 08/12/2025*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.