Description

Key Responsibilities

• Analyze legacy batch jobs, scripts, database procedures, and data workflows to understand current-state processing, dependencies, business logic, scheduling requirements, and operational constraints.
• Rewrite and migrate legacy batch workloads into AWS Batch using modern engineering practices while preserving business functionality and meeting existing service-level agreements.
• Develop, enhance, and maintain data pipelines and batch processing solutions using Java Spring Batch, Python, SQL, shell scripting, and AWS services.
• Support integration between on-premises legacy systems and AWS-based target platforms, ensuring reliable data movement, synchronization, monitoring, and operational continuity.
• Build and optimize data ingestion workflows to support the Rapid Data Ingestion platform, including file intake, validation, transformation, inventory tracking, and downstream consumption.
• Implement data quality checks to detect changes in vendor file formats, data integrity issues, missing or incomplete data, and other anomalies that may impact critical business processes.
• Enable and support data lineage capabilities by capturing source-to-target data movement, transformations, metadata, and audit-relevant processing details.
• Support disaster recovery implementation for the Rapid Data Ingestion platform in AWS to improve resiliency and continuity for critical and audit-sensitive processes.
• Develop and maintain job scheduling and orchestration processes using Control-M or equivalent scheduling tools.
• Implement secure engineering practices, including application-specific database access, elimination of shared credentials, and enforcement of least-privilege access principles.
• Perform performance tuning to ensure rewritten jobs meet or exceed current batch cycle expectations, including completion within strict operational SLAs.
• Participate in data validation, reconciliation, defect triage, testing, production deployment, and warranty support activities.
• Collaborate with data analysts, systems analysts, architects, application teams, database teams, governance teams, and business stakeholders to ensure successful delivery.
• Create and maintain technical documentation covering design, mappings, dependencies, lineage, quality rules, operational procedures, and deployment details.

Required Technical Skills:

• Strong experience with Java Spring Batch for batch job development, migration, and modernization.
• Hands-on experience with AWS services, especially AWS Batch and Amazon S3.
• Strong SQL development experience, including Oracle SQL and PL/SQL concepts.
• Experience developing data engineering solutions using Python.
• Strong shell scripting experience using Bash, KornShell, or similar Unix/Linux scripting languages.
• Experience with Control-M or equivalent enterprise job scheduling and orchestration tools.
• Experience working with legacy batch processing environments and modernizing on-premises batch workloads to cloud-based platforms.
• Ability to analyze and convert legacy scripts, SQL loaders, stored procedures, and batch workflows into modern, maintainable data processing jobs.
• Experience with data ingestion, ETL/ELT development, data validation, reconciliation, and production support.
• Understanding of secure access patterns, credential management, least-privilege controls, and audit-focused data processing.
• Experience with CI/CD, code deployment, version control, and standard software engineering practices.

Education: Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Engineering, or a related field, or equivalent practical experience.

Certifications: AWS certification, Snowflake certification, or relevant cloud/data engineering certification is preferred but not mandatory.

Expected Deliverables:

• Modernized and rewritten batch jobs deployed to AWS Batch.
• Enhanced Rapid Data Ingestion platform capabilities.
• Data quality checks, validation routines, and exception handling processes.
• Data lineage and metadata capture support.
• File inventory management capabilities for incoming data feeds.
• Disaster recovery support for AWS-based ingestion processes.
• Secure application-specific access patterns and reduced credential-sharing risk.
• Control-M or equivalent job schedules and operational workflows.
• Technical documentation, deployment notes, runbooks, and support procedures.
• Data validation, reconciliation, performance tuning, and production support outcomes

Key Skills

Education

Bachelor's degree