Back
Popular early-career Data Engineer role in Hyderabad with common Databricks/SQL skills increases applicant competition.
Core data engineering skills are broadly transferable across industries despite pharma dataset familiarity preferred.
Explicit 1–3 years requirement plus mandatory SQL/Python and Databricks familiarity creates moderate filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and maintain scalable, reliable batch and incremental data pipelines for commercial pharmaceutical datasets.
Transform and curate large-scale structured and semi-structured data into analytics-ready tables applying data modeling best practices and governance standards.
Collaborate with analysts and business stakeholders to translate requirements, ensure data quality, and support adoption of published data products.
1–3 years of hands-on experience in data engineering or related roles building ETL/ELT pipelines and curated datasets.
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, or related field (or equivalent practical experience).
Proficiency in SQL and Python; experience with Databricks and Delta Lake concepts preferred.
Experience with large-scale pharma related datasets (claims, patient, HUB, specialty pharmacy) preferred; work experience related to biopharma/pharmaceutical data not mandatory but favored.
Experienced in designing operational data pipelines and applying incremental processing using Databricks and Delta Lake in cloud environments.
Familiar with implementing data quality and governance practices including automated validations, lineage, access controls, and secure handling of sensitive data (PHI/PII).
Capable of translating business requirements into technical data solutions and maintaining clear technical documentation for sustained data product usability.