We are seeking a Junior Data Analyst to join our growing Data team, supporting both traditional analytics and emerging AI-driven initiatives. This role is ideal for an early-career professional who is passionate about working with data and eager to build foundational experience in modern data architectures and AI-enabling frameworks, including data mesh and knowledge graph concepts.
You will help transform raw data into actionable insights, contribute to scalable data models, and support use cases that power analytics, automation, and AI solutions across the organization.
What you'll do:
Data Analysis & Insights:
Analyze datasets to identify trends, patterns, and actionable insights
Support business stakeholders with ad hoc analysis and reporting
Translate business questions into structured data queries
Dashboarding & Reporting:
Build and maintain dashboards using tools such as Tableau, Power BI, or similar
Ensure clarity, usability, and accuracy of visualizations
Data Preparation & Modeling Support:
Write and optimize SQL queries to extract and transform data
Assist in developing curated datasets for analytics and AI use cases
Support data validation and quality checks
AI & Modern Data Concepts (Exposure + Growth):
Contribute to initiatives involving knowledge graphs, semantic layers, or metadata-driven systems
Support implementation of data mesh principles (domain-oriented datasets, data ownership, discoverability)
Assist in preparing datasets for AI/ML use cases
Collaboration:
Work closely with Data Engineers, Analytics Engineers, and business teams
Participate in requirements gathering and solution design discussions
Documentation & Governance:
Document data sources, definitions, and transformations
Follow data governance and quality standards
What you'll bring:
Required:
Bachelor’s degree in Data Analytics, Computer Science, Statistics, or related field
0–2 years of experience in data analytics or related role
Strong foundational SQL skills
Experience with Excel and at least one BI tool (Tableau, Power BI, etc.)
Basic understanding of data structures and relational databases
Preferred:
Exposure to Python or R for data analysis
Familiarity with cloud data platforms (Snowflake, BigQuery, Redshift, etc.)
Understanding of modern data stack concepts AI & Data Platform Exposure (Nice to Have, Not Required)
Awareness of knowledge graphs or semantic data models
Familiarity with data mesh or distributed data ownership concepts
Exposure to AI/ML workflows or data preparation for AI use cases
Interest in metadata, data lineage, and data discoverability
