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Tier-1 brand, metro Bangalore and mid-level data engineer role yields high applicant competition.
Data engineering skills are transferable across industries though pharma domain knowledge could be beneficial.
Explicit 5+ years and mandatory AWS, Databricks, and data engineering skills create high filtering.
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Develop and maintain scalable data models and data pipelines using AWS native technologies to support multiple business functions and digital products.
Ensure data quality through monitoring, reconciliation, and production data management for key stakeholders and downstream systems.
Collaborate with cross-functional teams including frontend/backend engineers, product managers, and enterprise groups to design and deploy integrated, secure, and scalable data solutions following data governance principles.
Bachelor’s Degree in Engineering, Computer Science, or related field from an accredited institution.
5+ years of experience in data engineering, software development, data warehousing, data lake/mesh, and building data products following FAIR principles.
Strong expertise with AWS cloud technologies (e.g., DMS, Lambda, Databricks), data integration, data modeling, GraphQL, SQL, No-SQL, Python, PySpark, and DBA/schema design/dimensional modeling skills.
Proficient with Agile Scrum methodology, JIRA, Confluence, and understanding of good engineering practices including DevSecOps and SDLC.
Experienced in operating within Agile Scrum teams to deliver complex, integrated data products in cloud environments, especially AWS.
Demonstrates strong technical expertise in modern data engineering technologies and data governance frameworks, suitable for enterprise-scale digital transformation.
Comfortable collaborating with multiple stakeholder groups across enterprise architecture, security, DevOps, and data governance to meet performance, security, and compliance requirements.