Jobs · Information Technology · New York

Mainframe Data Modeler - (IBM DataStage, ETL, SSRS, COBOL)

Cloud and Things · Brooklyn, NY · 3 wk ago
Information Technology$75–$85/hrFull-time

12-month contract (potential for extension) in Brooklyn, NY 11201 (hybrid – local candidates only). Anticipated start date: October 1, 2026. W2 hourly rate: $75 – $85/hour.

About the role

We are seeking a Mainframe Data Modeler to support our client’s Data Management team with data modeling, profiling, cleansing, conversion, migration, and validation activities for a legacy replacement initiative and ongoing process improvement programs. The role will perform detailed field-level and metadata analysis, develop conceptual, logical, physical, and dimensional data models, and translate legacy business and data quality rules into source-to-target mappings and technical specifications.

Responsibilities

  • Participate in the identification, inventory, and classification of critical data.
  • Perform detailed field-level analysis, metadata analysis, and profiling of internal and external data sources.
  • Create conceptual, logical, physical, and dimensional data models.
  • Work with data subject matter experts to document data quality rules, business terms, valid values, and definitions.
  • Support data profiling, cleansing, conversion, migration, and validation efforts for legacy replacement and process improvement initiatives.
  • Optimize and tune existing ETL and SQL processes for performance.
  • Extract business rules from legacy code and create source-to-target mappings.
  • Transform business rules and data quality rules into ETL and SQL technical specifications.
  • Develop complex SQL data validations based on source-to-target mappings and target data models.
  • Provide technical and analytical support for data integrity and data quality initiatives.
  • Collaborate with subject matter experts, technical leads, and IT partners to identify and remediate data quality gaps using manual and automated solutions.
  • Support processes that proactively detect, correct, and prevent invalid data values.
  • Perform defect handling, technical troubleshooting, and problem resolution.

Requirements

  • 5+ years of source-to-target data mapping experience in mixed IBM mainframe and relational database environments.
  • 3+ years of experience developing ETL applications using IBM DataStage.
  • Experience creating data dictionary documentation that includes business terms, valid values, and definitions.
  • Experience converting and migrating VSAM data to relational and dimensional SQL distributed databases.
  • Experience extracting field references, calculated data, and business rules from COBOL programs and legacy code.
  • Experience with BMC Control-M workload automation software.
  • Experience with Git version control software.
  • Minimum of three (3) years of recent experience with pension administration systems.
  • Strong SQL knowledge, including complex queries, stored procedures, and complex data validations based on source-to-target mappings and target data models.
  • Proficiency in SQL Server Reporting Services (SSRS) report development.
  • Proficiency with mainframe applications and technologies, including COBOL, CICS, and DB2.
  • Ability to work across IBM mainframe, Windows Server, and SQL Server environments.
  • Strong understanding of data structures and their relationships to ETL applications.
  • Strong analytical skills with the ability to analyze requirements and propose solutions that adhere to established team methodologies.

Desirable Qualifications

  • Experience with data quality and data profiling tools.
  • Experience with data warehouses and data marts.
  • Prior experience working in a pension system, preferably a New York State or New York City pension system.

Benefits

  • Opportunities to lead impactful transformations in the public sector infrastructure.
  • Engagement with high-profile government initiatives, supporting meaningful change.
  • A collaborative environment that values ownership, initiative, and continuous learning.

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