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Tier-1 brand, Bangalore location, mid-level generalist data role with broad skills increases competition.
Core data engineering skills (SQL, Python, cloud) transfer easily across industries despite healthcare preference.
Explicit 3+ years plus mandatory SQL/Python/cloud skills increases screening strictness.
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Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines to support analytics, reporting, and AI/ML solutions.
Collaborate with business and technology stakeholders to translate requirements into reliable data solutions and support cloud-based data platforms including data warehouses and lakehouses.
Provide technical guidance to team members, troubleshoot production issues, and contribute to automation, CI/CD, and continuous improvement initiatives in the data engineering ecosystem.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or related field.
Minimum 3 years of experience in data engineering, software engineering, or big data development.
Proficiency in SQL and Python with experience in developing ETL/ELT pipelines and working with large-scale datasets.
Experience with cloud-based data platforms such as Azure, AWS, or Google Cloud.
Experienced in designing and optimizing data pipelines and data architectures for enterprise-scale analytics and AI/ML workloads.
Able to work independently on moderately complex data engineering challenges and provide technical mentorship within teams.
Familiar with data governance, data quality frameworks, cloud data technologies (e.g., Databricks, Spark, Snowflake), and operating in highly regulated environments such as healthcare or financial services.