Data Analyst / Consultant (Databricks, Data Matching, Entity Resolution)

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Smart IMS Inc.

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python Spark Databricks Pandas Microsoft SpaCy Entity Oracle AWS

Job Description

Executive Summary

Smart IMS Inc provides Digital technology & Cloud transformation services, Application & Infrastructure Management Services, Unified Communications and Insurance implementation services to customers across the Americas, Europe, Middle East, and Asia-Pacific regions. As the trusted technology and business partner of leading MNCs, including Global Investment Banks, Smart IMS is also a Microsoft Gold Certified Partner, Oracle Platinum Partner and AWS MSP Partner.


We are seeking a highly skilled Data Analyst / Consultant with expertise in entity resolution and data matching to support a critical data mapping initiative. The primary objective of this role is to accurately map internal entity IDs to external identifier sets, ensuring high-quality 1:1 relationships across datasets.

This is an immediate requirement with potential for extension into larger-scale data initiatives.


Key Responsibilities

  • Map internal entity identifiers to external identifier systems (e.g., ISINs and other financial entity data)
  • Perform entity matching using incomplete or partially structured data (e.g., entity names)
  • Apply NLP and fuzzy matching techniques to improve match accuracy
  • Ensure clean, reliable 1:1 mappings across datasets
  • Work on an initial dataset (2,000โ€“3,000 records) with scalability in mind
  • Clean, transform, and standardize unstructured or imperfect datasets
  • Collaborate with stakeholders to validate matching logic and outcomes
  • Document methodologies and matching rules for future scaling


Required Skills & Experience

  • Possess at least 2-5 years of relevant experience in entity resolution / record linkage / data matching
  • Hands-on expertise in fuzzy matching techniques and NLP approaches
  • Strong experience working with imperfect or unstructured datasets
  • Proficiency in Databricks or similar big data platforms (e.g., Spark)
  • Solid data wrangling and data engineering skills
  • Strong analytical and problem-solving abilities


Preferred Qualifications

  • Experience working in financial services or with financial datasets
  • Exposure to large-scale data mapping or master data management (MDM)
  • Programming skills in Python (libraries such as pandas, fuzzywuzzy, spaCy, etc.)

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