Build and maintain data pipelines (ETL/ELT) to ingest data from multiple sources
Develop and optimize SQL queries for analytics and reporting use cases
Assist in managing and scaling data warehouses and data lakes
Perform data validation, cleansing, and quality monitoring
Collaborate with Data Analysts, Data Scientists, and Product teams
Support cloud-based data solutions on AWS, GCP, or Azure
Document data models, pipelines, and technical workflows
Troubleshoot and resolve pipeline failures or data discrepancies
Follow best practices related to data security, governance, and compliance
Master's degree (required) in Data Science, Computer Science, Information Systems, Engineering, Analytics, or a related field
Strong proficiency in SQL (joins, window functions, aggregations)
Working knowledge of Python for data processing and automation
Understanding of data modeling, ETL concepts, and database design
Familiarity with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle
Exposure to at least one cloud platform (AWS, GCP, or Azure)
Knowledge of Git or other version control systems
Strong analytical thinking and problem-solving skills
Excellent written and verbal communication skills
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