Assistant Manager, Data Engineer Informatica to AWS Glue Migration

Inviting applications for the role of Assistant Manager, Data Engineer - Informatica to AWS Glue Migration

Job Summary:

We are seeking an experienced Data Engineer whose primary responsibility is to design and develop ETL jobs that load data from FTP/SFTP locations into Amazon S3 and subsequently transform and load data from S3 into on-premises SQL Server databases using AWS Glue. The role also involves migrating existing Informatica PowerCenter workflows to AWS Glue while ensuring secure, reliable, and high-quality data processing.

Responsibilities:

• Plan and migrate existing Informatica workflows to AWS Glue (PySpark/Scala).

• Load flat files from FTP/SFTP into Amazon S3 with proper schema, partitioning, and data quality checks.

• Build and optimize AWS Glue Jobs, Crawlers, and Data Catalog tables with error handling and retries.

• Orchestrate ETL workflows using AWS Glue Workflows, Step Functions, EventBridge, or Glue Triggers.

• Connect AWS pipelines securely to on-prem SQL Server using JDBC, VPN/Direct Connect, and Secrets Manager.

• Design and optimize ETL to SQL Server, including upserts, bulk loads, and performance tuning.

• Implement data quality checks, logging, monitoring, and reconciliation using CloudWatch and Glue metrics.

• Optimize jobs for performance and cost efficiency.

• Create technical documentation and support UAT, cutover, and hypercare.

• Collaborate with security/network teams for IAM, VPC, subnets, security groups, and key management.

Qualifications we seek in you!

Minimum Qualifications

• Good years of experience in ETL / Data Engineering with hands-on experience in AWS Glue (PySpark).

• Strong SQL skills with experience working on SQL Server.

• Experience migrating Informatica PowerCenter (or similar ETL tools) to AWS Glue.

• Bachelor%27s degree in computer science, Engineering, or related field.

• Experience loading data from FTP/SFTP sources into Amazon S3.

• Hands-on experience with AWS Glue Jobs, Crawlers, Data Catalog, and CloudWatch.

• Experience connecting AWS pipelines to on-premises databases using JDBC and secure credentials.

• Good understanding of data validation, error handling, and data modeling concepts.

• Strong documentation and communication skills.

Preferred Qualifications/ Skills:

• Experience with AWS Step Functions, Lambda, or EventBridge.

• Exposure toAWS DMS, Athena, or Lake Formation.

• Familiarity with CI/CD and Infrastructure as Code tools.

• Experience with PySpark performance tuning.

• Exposure todata quality or monitoring tools.

• Experience working in regulated or compliance-driven environments.