Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
Updated: 13/01/2026
Design, develop, and maintain data pipelines to ingest, process, and transform structured and unstructured data using Python, SQL, Spark, and cloud-native services.
Build and optimize ETL/ELT workflows supporting analytics, reporting, and machine learning use cases.
Perform data profiling, validation, and quality checks to identify anomalies and implement corrective transformations.
Develop and deploy machine learning models for predictive analytics, classification, forecasting, and optimization.
Collaborate with business analysts, product teams, and engineers to deliver scalable data solutions.
Implement data modeling solutions in cloud data warehouses and data lakes.
Optimize data processing performance through query tuning, partitioning, indexing, and distributed compute jobs.
Automate data workflows using scheduling, logging, and alerting mechanisms.
Document pipelines, models, and technical processes for maintainability and audit readiness.
Ensure compliance with data governance, security, and privacy standards.