data engineer for enterprise data platforms

No description

• Develop and maintain enterprise data pipelines;
• Build ETL/ELT workflows and system integrations;
• Design data transformation and synchronization processes;
• Support data warehouse and master data solutions;
• Perform large-scale data migrations;
• Implement secure data transfers across cloud environments;
• Troubleshoot production data workflows;
• Improve pipeline performance and reliability;
• Implement data quality and validation processes;
• Collaborate with Data, Cloud, DevOps and Architecture teams;
• Document technical solutions and data flows.

• 5+ Years of experience in Data Engineering / Data Integration;
• Strong Python and SQL skills;
• Hands-on experience with ETL/ELT and data pipeline development;
• Experience with data warehouses and large datasets;
• Production environment experience;
• Knowledge of data modeling and integration;
• Experience with AWS, Azure or GCP;
• Understanding of cloud architecture and networking;
• Practical experience with VPC / Virtual Network;
• Experience with cloud-to-cloud, cross-account or cross-region data migration;
• Understanding of IAM and secure connectivity;
• Strong analytical and troubleshooting skills;
• Data Engineering profile required, not a pure MDM or BI specialist;
• Strong experience with Python, pipelines, cloud and migration is essential;
• Nice to have: Databricks, Snowflake, AWS Glue, Azure Data Factory, Airflow, Kafka, Spark/PySpark, Terraform, Docker, Kubernetes, Informatica, Talend, SSIS.

• Long-term engagement.