JSM is seeking a contract Data Quality Analyst to help us raise the quality of the data underpinning our product. Data quality directly affects the reliability, security, usability, and trustworthiness of what we deliver to our users, and data accumulated over the past 9 years has eroded some data quality. This role will focus on projects and customer accounts that have been non-functional for five years or more, yet they — along with their dependent data — that persist in our active systems. The introduction of a new ERP system provides more opportunities to clean data related to customers and their access. We need an expert who can extract data from existing databases, use various fields and queries to identify functional areas and dormant data, determine what can be archived or removed, and more broadly make recommendations to improve overall data quality and maintenance practices. Working alongside the Product Owner and functional stakeholders, this role will assess the current state of our data, diagnose the root causes of quality issues,
and recommend the right set of improvements — from identifying and retiring obsolete data to normalization, standardization, de-duplication, and correction. This is a business-outcome driven role: the objective is to have measurably better, leaner, more trustworthy product data. Familiarity with Maximo, Windchill, or the marine/maritime domain is a robust advantage.
What You Will Do:
- Identify dormant and obsolete data. Find functional areas that have been inactive for extended periods — five years or more — and map the dependent data tied to them, so we know exactly what can be safely archived or removed.
- Understand our product data. Study the data that powers our product — across primary and related data sets — and build a clear picture of its structure, relationships, and dependencies.
- Tell us where we stand. Assess data quality against the dimensions that matter to us — accuracy, completeness, consistency, uniqueness
📌 Portal Data Analyst (Hyderabad)
🏢 jsm
📍 Hyderabad