Why This Role Stands Out
Step into a pivotal leadership role as a Lead MDM Engineer, driving critical initiatives within a reputable company and gaining invaluable experience with Semarchy xDM. If you possess strong data engineering, analysis, and leadership skills, you'll thrive in this hands-on position that offers a hybrid work model for excellent flexibility. This is a fantastic opportunity to make a significant impact and advance your career.
Quick Overview
Job Description
MDM Lead Engineer
Location: NY – hybrid 3 days onsite
12 months
Job Description
We are looking to hire an MDM Lead Engineer for our Client Master team and would like your support in identifying strong candidates for us to interview.
This is a senior, hands-on technical leadership role. We are looking for someone who can become a trusted technical owner for our MDM platform and reliably drive initiatives from design through execution.
The ideal candidate should have strong Semarchy xDM and Master Data Management expertise, combined with solid data engineering, data analysis, team leadership, and business-facing communication skills.
This role requires the candidate to work in person in our New York office 3 days per week. Please only submit candidates who are able and willing to meet this requirement.
Key Requirements
- 10+ years of relevant engineering and data experience.
- Strong hands-on expertise with Semarchy xDM.
- Deep understanding of Master Data Management concepts, including match/merge, survivorship, golden records, hierarchies, data quality, stewardship, workflows, and publishing/integration patterns.
- Proven experience implementing enterprise MDM solutions end-to-end, from requirements and data analysis through production implementation and support.
- Strong SQL, data profiling, and data analysis skills, with the ability to investigate anomalies, identify patterns, and drive root-cause analysis.
- Strong understanding of the underlying data domain and the ability to go beyond application configuration to understand source data, business processes, and downstream consumption.
- Solid data engineering background with experience building and supporting production-grade data pipelines.
- Experience with technologies such as Snowflake, Azure, ADF, dbt, Fivetran, Python, APIs, or comparable modern data technologies.
- Strong understanding of data modeling, data quality, data governance, metadata, lineage, and stewardship concepts.
- Ability to manage multiple priorities and switch effectively between architecture, engineering, analysis, team leadership, and stakeholder engagement.
- Comfortable operating in a high-expectation, fast-moving environment with competing priorities and tight delivery timelines.
- Ability to provide hands-on technical leadership to onshore and offshore engineering teams.
- Experience reviewing and guiding technical designs, data models, SQL, pipelines, implementation approaches, and code.
- Strong ownership mindset — someone who can take ambiguous problems, bring structure, make sound technical decisions, and drive them through completion.
- Strong curiosity about data and a genuine passion for solving difficult data problems.
- Strong problem-solving skills with a focus on identifying and addressing root causes rather than implementing short-term fixes.
- Outcome-driven, dependable, and committed to delivery.
- Excellent written and verbal communication skills.
- Strong presentation skills and the ability to communicate effectively with Product Owners, Data Stewards, business stakeholders, architects, engineering teams, and senior technology leaders.
- Ability to translate business requirements into scalable and maintainable technical solutions.
- Forward-looking mindset with an interest in modern engineering practices and AI-native approaches to data quality, automation, engineering productivity, and problem solving.
Strongly Preferred
- Financial Services, Asset Management, Wealth Management, or Capital Markets experience.
- Experience with Client, Customer, Organization, Contact, Account, Party, or similar master data domains.
- Salesforce integration experience.
- Experience modernizing or re-architecting an existing MDM implementation.
- Experience integrating MDM platforms with cloud data warehouses, operational systems, APIs, and downstream analytical platforms.
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