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Data Architect (Data Conversion lead)

New York Technology PartnersPortsmouth, NH🇺🇸United StatesPosted Sep 23, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Portsmouth, NH, United States
Posted
Yesterday
SQLETLStakeholder Management

Job Description

Title: Data Architect (Data Conversion lead)

Location: Portsmouth (Hybrid)

Position: Contract

 

JOB DESCRIPTION: 

Data Conversion Lead

 

Job Overview

The Data Conversion Lead is responsible for planning managing and executing endtoend data conversion and migration activities as part of largescale system implementations or transformations This role ensures that data from legacy systems is accurately extracted transformed validated and loaded into target systems while maintaining data integrity quality and compliance The Data Conversion Lead works closely with business stakeholders application teams architects and vendors to ensure successful data migration aligned with project timelines and business objectives

 

Key Responsibilities

Lead and manage the overall data conversion strategy approach and execution

Analyze source and target data models and define data mapping and transformation rules

Coordinate data extraction cleansing validation and reconciliation activities

Work closely with business teams to understand data requirements and usage

Oversee development and execution of data conversion scripts and tools

Validate converted data through reconciliation balancing and exception analysis

Identify track and resolve data issues and risks proactively

Support mock conversions system testing UAT and golive cutover activities

Ensure adherence to data governance audit and compliance standards

Provide status updates metrics and documentation to project leadership

 

Required Skills  Experience

8-12 years of experience in data migration or data conversion roles

Strong understanding of data modeling ETL concepts and RDBMS

Handson experience with SQL and database tools

Proven experience leading conversion activities for enterprise systems

Excellent communication analytical and stakeholder management skills

 

Success Factors

Accurate and timely data conversion with minimal postgolive defects

Strong collaboration across technical and business teams

High data quality and stakeholder confidence in converted data

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