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Data Conversion Specialist - Public Pension Administration

Estaff LLCUnited States🇺🇸United StatesPosted 26 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
6 hours ago
SQLSQL ServerT-SQLETLAirflowApacheAzureC#.NETPower BIReconciliationRoot Cause AnalysisTriagedbt

Job Description

We are seeking a Data Conversion Specialist with hands-on experience in large-scale public pension administration system modernization programs, specializing in ETL development, data reconciliation, and legacy system data migration. The position is 100% Remote.

Can work with C2Cs

This technical role is the primary data conversion resource, responsible for building and maintaining the ETL pipelines, conversion scripts, and reconciliation tooling that drive the Retirement Insurance System Enhancement (RISE) data migration workstream.

Must demonstrate direct experience developing data conversion programs for pension or benefits system modernization projects, including executing source-to-target mapping, SSIS/BIML development, SQL Server and T-SQL optimization, and participation in mock runs and UAT cycles through production cutover. The Worker will follow all organizational Standard Operating Procedures related to deliverable approvals, reviews, and associated workflows.

Must have technical experience to collaboratively develop and maintain conversion assets, troubleshoot ETL exceptions, and work closely with the Technical Architect, ML/AI Engineer, and ERS data stewards to resolve data issues and ensure converted data aligns with functional requirements and business rules. Strong attention to detail, structured debugging discipline, and cross-functional communication skills are expected.

 

Functional Responsibilities:

We are seeking a Data Conversion Specialist with direct hands-on experience in large-scale pension or benefits system data migration programs. The worker will execute the technical data conversion workstream for the client''s program, developing and maintaining ETL pipelines, reconciliation scripts, and conversion monitoring tools across all Central Data Repository (CDR) cycles.

 

The worker will be responsible for:

 

     Develop and maintain packages and scripts for automated, repeatable data extraction, transformation, and load processes across legacy source data and target schema

     Implement and optimize stored procedures, views, indexes, and SQL queries to support high-volume ETL operations and data reconciliation workflows

     Develop automation scripts for conversion process orchestration, custom components, and backend data processing logic across multiple CDR cycles

     Execute source-to-target mapping in alignment with CDR specifications, applying authorization and exclusion logic to filter ineligible, duplicate, or obsolete member and employer records

     Participate in data reconciliation activities including record count validation, key field comparison, exception reporting, screen validation within the target TELUS Health Ariel platform

     Support multiple extract and load processes across development, test, and production environments, ensuring converted data aligns with functional requirements and ERS business rules

     Collaborate with QA teams, functional testers, and the ML/AI Engineer to verify data migration results, resolve defects, and implement fixes during mock runs and UAT cycles

     Generate and maintain conversion monitoring reports tracking ETL job completion, exception handling, and data validation statistics for program leadership visibility

 

The Worker should have strong hands-on experience in pension or benefits system data conversion development within a structured, governance-driven program environment.

 

Minimum Qualifications

Please do not submit a candidate that does not meet the following minimum requirements.

Years

Skills / Experience

4+

Data conversion development for large-scale pension administration system modernization programs; source-to-target mapping, ETL execution, exception handling, and validation across multi-billion-record legacy data sets.

4+

SSIS package development and BIML scripting for automated, repeatable data extraction, transformation, and load processes across legacy pension and structured relational data environments.

4+

SQL Server and T-SQL development include complex stored procedures, views, indexing strategies, query optimization, and execution plan analysis to support high-volume ETL and reconciliation workflows.

3+

C# and .NET development for data conversion automation scripts, SSIS custom components, and backend data processing logic within a structured SDLC environment.

3+

Legacy system data migration experience including source environments; multi-environment extract and load processes; participation in mock runs, UAT cycles, and production cutover activities.

2+

Data reconciliation including record count validation, key field comparison, exception reporting, authorization and exclusion logic, and validation within a large-scale pension or benefits modernization platform.

1+

Large-scale public pension administration system modernization data conversion experience.

1

Database Administrator experience.

The Worker should have strong hands-on experience in pension or benefits system data conversion development within a structured, governance-driven program environment.

 

Preferred Qualifications

Years

Skills / Experience

3+

Azure Data Factory, PySpark, or Apache Airflow pipeline development for ELT/ETL orchestration, incremental loading strategies, and data quality validation in cloud or hybrid data environments.

2+

Power BI or SSRS dashboard and report development including ETL job completion tracking, exception rate reporting, and data quality KPI visualization for program leadership and QA teams.

2+

Cloud data warehouse development using dbt Core for staging, intermediate, and reporting layer transformations with incremental load strategies (SnowPro Core or Microsoft Fabric certification a plus).

2+

Defect triage and root cause analysis using SQL scripts and SSIS debugging techniques; cross-functional collaboration with QA, functional testers, and business analysts during mock loads and UAT resolution cycles.

 

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