Job Description

Job Title: Data Engineer (EBCDIC Data Processing)

Location: Remote

Duration: Long Term Contract

Role summary

• Design, build, and operate reliable archiving and purging solutions on Microsoft SQL Server for datasets stored/represented in EBCDIC format, using SQL Server stored procedures and Python automation.
• Own batch execution and scheduling via Control M, ensuring performance, auditability, retention compliance, and safe deletion practices.

Required Skills:

• Build and maintain SQL Server stored procedures for data archiving, purge eligibility determination, and purge execution (soft/hard deletes as required).
• Handle EBCDIC data processing requirements (e.g., EBCDIC ASCII/Unicode conversion, fixed-length records, packed decimals/COBOL-style encodings when applicable) and ensure data integrity post-conversion.
• Develop Python utilities for orchestration, validation, reconciliation, exception handling, and operational automation (e.g., pre/post checks, file-based extracts, run reports). Implement purge controls: retention rules, legal hold/exclusions, referential integrity management, dependency ordering, and rollback/restore strategy.
• Optimize performance for large volumes (partitioning strategies, indexing, batching, minimal logging approaches where appropriate, transaction scoping). Integrate and run jobs in Control M: job definitions, calendars, dependencies, resource limits, alerting, rerun/restart logic.
• Create operational runbooks, monitoring dashboards/metrics, and support production incidents (root cause, fixes, postmortems). Ensure security and compliance: least-privilege access, audit trails, PII handling, and evidence for retention/purge execution.
• Collaborate with DBAs, data governance, and application teams to validate retention policy interpretation and downstream impacts.

Required technical skills

• SQL Server: T SQL, stored procedures, transactions, error handling, temp tables, indexing, query tuning, SSMS, SQL Agent fundamentals (even if Control M is primary).
• EBCDIC: understanding of common code pages (e.g., 037/1047), conversion pitfalls, fixed-width layouts, and validation strategies.
• Python: building maintainable scripts/modules for ETL-style tasks, database connectivity (ODBC), logging, configuration, and testability.
• Batch scheduling: Control M job creation/execution, dependencies, alerts, reruns, and operational support.
• Data lifecycle: archiving patterns, retention, purge frameworks, auditability, and safe-delete patterns.

Nice-to-have skills

• Experience with very large tables (VLDB), table partitioning/switching, and archival to cheaper storage tiers.
• Familiarity with mainframe-originated data models, COBOL copybooks, and packed numeric formats.
• CI/CD for database objects (DACPAC/SSD T or equivalent), Python packaging, and automated testing.
• Knowledge of data governance tools/processes and legal hold workflows. Experience in regulated environments (SOX, PCI, HIPAA, GDPR-like retention controls).

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