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Protocol Intelligence

Data-driven signals on your job's competitiveness

CV Match Score

Estimated fit based on your resume

Structured overview of role & requirements

1–3 yearsDirect Career PageEst. 8–14 LPA

Against your primary resume

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Role Fit

Experience

Industry Relevance

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Data-driven signals on your job's competitiveness

Competition Intensity

(High)

Background Fit Sensitivity

(Moderate)

Shortlisting Strictness

(Moderate)

Structured overview of role & requirements

Develop and maintain scalable, well-documented analytical data models and pipelines to support self-service analytics.

Collaborate with business stakeholders to gather requirements and deliver centralized data-products enabling data-driven decision-making.

Use ELT frameworks (preferably DBT) on AWS-based infrastructure to transform raw/semi-structured data and partner with AI/ML teams for data needs.

1-3 years of experience in analytical engineering, data modeling, or related role.

Proficiency in SQL, SPARK, Python; experience with data engineering tools (AWS, Airflow) and BI visualization tools (Tableau, Power BI, Looker).

Preferred degree in Computer Science, Physics, Math, Data Science, Pharmaceutical Science, or Engineering.

Experience or exposure to DBT; experience with version control (e.g. Git) and Agile development.

Early-career analytical engineer capable of bridging data engineering and analytics to deliver business-ready datasets.

Comfortable working within cross-functional teams and translating business requirements into technical solutions.

Familiarity or interest in AI/ML integration and willingness to develop communication skills for diverse stakeholders.