Data Engineer

Job Overview We are seeking a highly skilled Data, AI Amazon Connect Engineer with 3+ years of experience in data engineering, cloud analytics, AI/ML, and customer decision intelligence. The ideal candidate will integrate multiple enterprise data tables and sources into Amazon Connect decisioning workflows, design scalable Databricks-based data pipelines, and deliver actionable insights from the system to improve customer experience, operations, and business performance. Job Requirements Design and implement Amazon Connect flows, routing logic, customer journey orchestration, and decision frameworks using customer, transaction, and operational data. Connect multiple data tables and sources such as SAP, CRM, ERP, SQL databases, APIs, event streams, and cloud storage into decision workflows. Build scalable ETL/ELT pipelines using Databricks, PySpark, Spark SQL, Delta Lake, and Databricks Workflows for batch and near real-time use cases. Develop predictive analytics, segmentation, next-best-action, recommendation, NLP, and GenAI-based insight solutions to support business decisions. Use AWS services such as Lambda, S3, Glue, Redshift, Kinesis, SageMaker, Athena, Step Functions, IAM, and CloudWatch for secure and scalable architecture. Create dashboards, executive reports, and operational insights using Power BI, Amazon QuickSight, or Tableau; translate data outputs into business recommendations. What your background should look like Minimum 3+ years of professional experience in data engineering, analytics, AI/ML, or cloud data platform engineering. Hands-on experience integrating enterprise data tables and source systems into customer engagement or decisioning platforms. Strong experience with Amazon Connect implementation, integrations, flows, and customer interaction analytics. Strong hands-on experience with Databricks, Delta Lake, PySpark, SQL, and lakehouse data architecture. Experience building AI/ML or advanced analytics solutions that generate actionable business insights. Bachelor''s degree in Computer Science, Engineering, Data Science, Information Technology, or a related field.