We are seeking an experienced Cloud Data Engineer to the architecture, development, Data migration,
ETL pipeline in cloud and optimization of a next-generation data platform. This is a development role for
an individual with over 4 years of deep data engineering and data migration, data pipeline in AWS
expertise, capable of driving technical direction, and delivering high-impact solutions in a fast-paced
Key Responsibilities
Platform Development
Knowledge of best practices for our end-to-end data pipelines in Cloud, ensuring
scalability, reliability, and security across the platform.
Aggressively folowing the project timeline to ensure rapid delivery of data migratation
in AWS RDS.
Working with Data Analysts, and business stakeholders to translate complex
requirements into robust, production-ready ETL data solutions.
Data Pipeline Development
Ingestion & Transformation: Design, build, and optimize high-volume data ingestion and
transformation jobs using tools like dbt Core, iceberg, AWS Glue, ensuring data quality
and integrity.
Building ELT/ETL pipelines and using workflow orchestration tools like Apache Airflow or
dbt
Optimize large-scale data processing algorithms and cloud data warehouse performance.
Workflow: Develop and maintain sophisticated data pipelines using AWS glue/lambda,
focusing on modularity and reusability.
Streaming & Real-time Integration: Implement and manage real-time data flows utilizing
native AWS streaming services (e.g., Kinesis) for immediate data availability.
Data Security and Privacy: Data Anonymization, Compliance with Regulations
Positive knowledge of CI/CD for ETL pipeline automation and Data
migration
Drive the Data Ecosystem Management & Monitoring
Open Table Formats & Management: Implement and maintain the Iceberg open table
format, utilizing tools for efficient schema evolution and data management.
Compute Engine Optimization: Optimize query performance and cost efficiency across