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Data Analyst (NL-SQL)

Innodata Inc.

0 - 3 years

Alipur

Posted: 16/05/2026

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Job Description

Data Analyst (Contractual-2 Months)


Responsibilities:

  • Dive deep into existing dashboards to understand the underlying data, key metrics, and typical user interactions.
  • Infer and document common user journeys and potential questions (use cases) users would ask of the data presented in the dashboards.
  • Translate identified use cases into precise Natural Language (NL) prompts.
  • Develop accurate and efficient SQL queries that correctly retrieve the data to answer the NL prompts, exploring table schemas and business rules as needed.
  • Create, label, and validate a large volume of high-quality NL-SQL pairs.
  • Collaborate with business stakeholders and dashboard owners to confirm use cases, clarify business logic, and refine NL prompts.
  • Proactively identify and explore new potential use cases and insights from the dashboards.
  • Utilize AI-powered tools and techniques to enhance efficiency and quality in the NL-SQL pair generation process.
  • Document findings, schemas, and business rules encountered.


Qualifications:

  • Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Informatics, Engineering) or equivalent practical experience.
  • 3+ years of experience in data analysis, business intelligence, or a similar role.
  • Strong proficiency in SQL, including writing complex queries, joins, and aggregations.
  • Proven ability to analyze and interpret data presented in dashboards and reports.
  • Excellent communication and interpersonal skills, with the ability to facilitate discussions with technical and non-technical stakeholders.
  • Analytical and inquisitive mindset with a passion for understanding data and user needs.
  • Experience with or a strong interest in AI and machine learning concepts.
  • Ability to work independently and manage multiple tasks in a fast-paced environment.


Preferred Qualifications:

  • Familiarity with Data Center operations, metrics, or data.
  • Experience with data labeling or dataset creation for machine learning models.
  • Familiarity with data platforms and tools.

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