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Tier-1 brand, metro location, popular data engineering role, and broad multi-tool requirements increase competition.
Core data engineering skills are transferable, though pharma R&D domain knowledge moderately increases fit sensitivity.
Mandatory 8+ years plus extensive specific tech stack requirements make shortlisting filters strict.
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Lead design and development of scalable ETL/ELT data pipelines and workflows for ingesting, processing, and storing complex R&D datasets.
Collaborate in agile Data & AI product delivery pods to build data products serving multiple R&D business areas, providing feasibility input and engineering progress updates.
Support junior engineers and optimize data workflows to ensure high performance, reliability, and alignment with product requirements.
Bachelor's degree in software engineering or related field or equivalent experience.
Minimum 8 years of experience in data product engineering, software engineering, or related fields.
Mandatory strong skills in Python, SQL, AWS cloud services (including S3, Lambda, Glue, EC2, IAM, SQS, API Gateway, EventBridge, EMR, MWAA), Snowflake data warehouse, Informatica IICS, Apache Airflow, Terraform, CI/CD pipelines, and core data engineering concepts like data modeling and batch/stream processing.
Work Experience Required: Minimum 8+ years, Location: Hyderabad, India.
Experienced in data engineering within R&D or related scientific environments, with understanding of R&D business data landscape preferred.
Comfortable working in Agile product delivery teams with cross-functional collaboration and iterative product development.
Practitioner of scalable cloud-native data architectures and engineering practices leveraging a broad AWS-based technology stack and advanced tools like dbt and Terraform.