Senior Analyst MDM Sys Engineer

Job description

Key Responsibilities

Integration Engineering & ArchitectureEnd-to-End Data Pipelines: Design, implement, and maintain scalable batch and real-time data integration pipelines (APIs, ETL/ELT) connecting source systems (Mainframe, legacy SQL) to MDM/PIM platforms and Snowflake.Source-to-Target System Mapping: Map data lineage, JSON/REST API payloads, and complex business transformation rules across enterprise boundaries to deliver clean, synchronized master data sets.Modernization & Automation: Lead efforts to transition legacy, decentralized transformations (Alteryx, local SQL scripts) into optimized Snowflake cloud tables and automated orchestration workflows. MDM & PIM Platform ManagementSystem Integrity & Governance: Supervise and maintain structural data integrity, global taxonomy hierarchies, and attribute schemas within enterprise PIM/MDM platforms (e.g., Enter Works, Precisely or similar), enforcing automated validation rules and business logic.Data Quality Auditing: Write intermediate-to-advanced SQL queries and profiling scripts to perform automated data validation, backend regression testing, and anomaly detection across staging and production environments.Syndication & Outbound Feeds: Configure and manage outbound data syndication feeds to downstream enterprise applications, including Salesforce, e-commerce platforms, and reporting layers. Requirement Engineering & Technical SupportTechnical Scoping: Deconstruct complex business requirements, stakeholder asks, and domain rules into explicit technical specifications, system flow diagrams, and actionable Jira sprint tasks.Incident Engineering & Root Cause Analysis: Investigate and resolve high-priority data pipeline failures, sync gaps, and integration anomalies submitted via ITSM tools (Ivanti) and Jira, enforcing target SLAs.Standardization & Change Management: Evaluate downstream technical and reporting impacts prior to executing schema updates, taxonomy modifications, or API ingestion changes. Maintain detailed technical documentation, system flows, and data dictionaries in Confluence.

Qualifications & Technical Requirements

Education: Bachelor’s degree in Computer Science, Information Systems, Software/Data Engineering, or a related technical field (or equivalent professional experience).Experience: 2–5 years of hands-on experience in data engineering, integration engineering, or systems analysis within an enterprise MDM, PIM, or cloud data warehouse environment.Technical Proficiencies:SQL & Data Querying: Strong proficiency writing complex SQL (joins, aggregations, window functions) for database validation, pipeline profiling, and schema analysis.MDM & Cloud Data Stack: Hands-on experience with enterprise MDM/PIM platforms (EnterWorks, Informatica, or similar) and cloud data platforms (Snowflake).Integration Protocols: Solid understanding of APIs (REST/GraphQL, JSON/XML), ETL/ELT pipeline mechanics, and automated data orchestration.Agile & ITSM Tools: Proficiency with Jira, Confluence, and service desk tools (Ivanti or similar) for managing sprint backlogs and incident tickets.Soft Skills: Strong systems thinking and analytical problem-solving skills, with the ability to bridge communications seamlessly between data engineering teams and non-technical business partners.