Aws Data Engineer + Informatica IDMC

Role: AWS Data Engineer

Exp :Min10yrs exp

Location: Bengaluru,

Mandatory Skills:

AWS Glue, Lambda, S3, Athena, Step Functions, Python, PySpark, SQL, Informatica IDMC, Terraform, Airflow, Kubernetes, Linux.

• Design and implement scalable enterprise data and archival platforms using AWS and Informatica.

• Build and maintain batch and near real-time data pipelines using AWS Glue, Lambda, PySpark,and IDMC services.

• Develop data ingestion, transformation, validation, and archival workflows.

• Lead technical architecture discussions and establish reusable engineering standards.

• Support large-scale enterprise data migration and archival initiatives.

• Improve platform reliability, scalability, observability, and operational support processes.

• Integrate structured and semi-structured data from multiple enterprise systems.

• Collaborate with infrastructure, security, network, DBA, and application teams.

• Drive automation and Infrastructure as Code practices using Terraform and CI/CD pipelines.

• Optimize data pipeline, storage, and query workload performance.

• Mentor engineering teams and influence best practices across delivery programs.

• Support governance, compliance, audit, retention, and data lifecycle management requirements.

• Define operational processes including monitoring, recovery, and support readiness.

Required Skills

Cloud and Data Engineering

• Strong AWS experience (Glue, Lambda, S3, Athena, Step Functions, CloudWatch).

• Strong Python and PySpark development experience.

• Experience building scalable ETL and ELT pipelines.

• Strong SQL and data modeling skills.

• Experience with distributed data processing frameworks.

Informatica IDMC

• Strong experience with Informatica Intelligent Data Management Cloud (IDMC).

• Experience with Cloud Data Integration, Mass Ingestion, Application Integration, Data Quality,

and Cloud Data Governance.

Experience designing and supporting enterprise archival and data retention solutions using IDMC.

• Experience integrating IDMC with AWS services and enterprise data platforms.

• Understanding of metadata management, lineage, and governance.

Platform and DevOps:

• Experience with CI/CD pipelines and automation.

• Infrastructure as Code using Terraform or similar tooling

• Experience with Linux and shell scripting.

• Containerization and Kubernetes experience preferred.

• Monitoring and logging experience with tools such as Grafana, ELK, or CloudWatch.

Leadership and Delivery:

• Strong stakeholder management and communication skills.

• Experience leading technical delivery across multiple teams.

• Strong troubleshooting and problemsolving skills.

• Experience managing platform dependencies, operational risks, and delivery milestones.

• Ability to define engineering standards and improve delivery processes.

• Experience working in enterprise governance and controlled environments.

Preferred Experience:

• Enterprise archival and data retention platforms.

• Banking, healthcare, telecom, or other regulated industries.

• Data governance and compliance frameworks.

• Large-scale platform modernization initiatives.

• Highavailability and disaster recovery environments.

• Supporting operational and production platforms.

Typical Technology Stack:

AWS Glue, Lambda, S3, Athena, Step Functions, Python, PySpark, SQL, Informatica IDMC, Terraform, Airflow, Kubernetes, Linux.

Ideal Candidate Profile

• Ten or more years in data engineering and enterprise data platforms.

• Strong mix of architecture, handson engineering, and operational support.

• Experience designing scalable cloudnative data solutions.

• Proven experience delivering enterprise integration and archival solutions.

• Comfortable working in complex multiteam enterprise environments.

• Ownership mindset with strong focus on reliability, scalability, and delivery quality.