Role: Senior Data Architect / Senior Data Engineer
Duration: 12+ Months
Location : Frisco / Atalanta/ Overland / New Jersy Remote
Position Summary
We are seeking a highly experienced Senior Data Architect / Senior Data Engineer to help design, build, and scale our enterprise data platform. This role will be a senior technical leader and hands-on contributor responsible for developing modern data architectures, establishing engineering standards, and delivering trusted, reusable data products.
The ideal candidate has deep experience with dbt, Databricks, data modeling, and cloud-based data platforms. Experience designing or implementing entity resolution, record linkage, identity matching, or deduplication solutions is a significant advantage, particularly using open-source frameworks such as Splink or Zingg.
Additional Key Responsibility: Entity Resolution and Master Data
Design scalable entity-resolution and record-linkage solutions across large, complex datasets.
Develop matching, deduplication, survivorship, and identity-resolution patterns for customer, account, product, location, or other enterprise entities.
Partner with master data management and governance teams to improve the accuracy and consistency of enterprise records.
Evaluate deterministic, probabilistic, and machine-learning-based matching approaches.
Define processes for match scoring, threshold selection, exception handling, clerical review, and ongoing model evaluation.
Integrate entity-resolution outputs into curated data products, master data workflows, analytics datasets, and downstream business processes.
Preferred Qualifications
Hands-on experience with Splink, Zingg, or a comparable entity-resolution or record-linkage framework.
Strong understanding of probabilistic record linkage, fuzzy matching, blocking strategies, match scoring, clustering, and deduplication.
Experience implementing entity resolution at scale using Databricks, Spark, or distributed data-processing technologies.
Experience measuring and improving matching precision, recall, false-positive rates, and false-negative rates.
Experience integrating entity-resolution solutions with master data management, customer 360, identity resolution, or golden-record initiatives.
Experience with Microsoft Fabric, Power BI semantic models, or enterprise BI platforms.
Experience integrating Databricks with Microsoft Azure services.
Familiarity with Unity Catalog or comparable data cataloging and governance capabilities.
Experience developing enterprise metric catalogs or certified analytical datasets.
Experience mentoring engineers and influencing technical standards across teams.
Ideal Candidate Profile
The ideal candidate is an experienced architect who still enjoys building. They are comfortable defining enterprise standards, but they are equally comfortable writing SQL, reviewing dbt models, troubleshooting pipelines, and improving development frameworks.
A particularly strong candidate will have solved difficult identity-resolution or duplicate-record problems and will understand that entity resolution is not simply a fuzzy join. They will be able to select appropriate matching attributes, design blocking rules, tune thresholds, evaluate match quality, and operationalize results within an enterprise data platform
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