Design and develop scalable data pipelines using AWS services (Glue, EMR, Lambda, S3, etc.)
Build ETL/ELT processes using PySpark and Python to ingest, transform, and process large-scale datasets.
Integrate and manage data workflows between AWS and Snowflake data warehouse.
Collaborate with data analysts, data scientists, and business stakeholders to gather requirements and deliver data solutions.
Implement data quality checks, monitoring, and performance tuning for data pipelines.
Automate data ingestion from various sources including APIs, flat files, and databases.
Ensure secure, compliant, and cost-efficient data solutions aligned with industry best practices.
Participate in code reviews, CI/CD processes, and team agile ceremonies.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time