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Tier-1 employer, generic Software Engineer title, Hyderabad location and broad data skillset make competition high.
Core data engineering skills transfer across industries, though pharma domain familiarity is advantageous.
Explicit 1–3 years requirement plus mandatory SQL, Spark, Python and cloud/tooling implies medium strictness.
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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.