Associate Data Analyst (Emirati National)

You will collaborate with a diverse ecosystem of engineers, product experts, and business to solve real problems that impact our customers and business outcomes.

Your responsibilities

• Model and transform data for analysis

• Build and maintain clean, reusable datasets (fact and dimension tables) that power reporting and self-serve analytics.

• Contribute to a scalable metrics layer: define, document, and align business definitions (for example, "active user", "approval rate", "default rate").

• Support analytics and decision making

• Answer ad-hoc questions with clear analysis and explainable methodology.

• Turn common questions into reusable, self-serve assets: dashboards and AI-enabled workflows (a curated dataset + definitions that an AI assistant can query correctly, plus validated example analyses).

• Create AI-friendly data products (well-defined datasets, metrics, and documentation) that teams can query through AI tools.

• Enable AI-ready analytics

• Package datasets and metrics so they can be reliably used by AI tools (clear grain, business definitions, data contracts, examples).

• Write AI-friendly documentation: glossary, metric definitions, common queries, and pitfalls.

• Partner with AI and platform teams to ensure critical tables are discoverable, permissioned correctly, and safe to use.

• Ensure data quality and reliability

• Write basic tests, checks, and monitoring for key datasets and critical metrics.

• Troubleshoot data issues and improve reliability from source to reporting.

• Work effectively with engineering and product

• Collaborate with data engineers on schema changes, event tracking, and pipeline improvements.

• Translate ambiguous business questions into measurable analyses, and communicate findings clearly.

• Use AI tools thoughtfully

• Use AI to accelerate SQL drafting, code scaffolding, and documentation.

• Validate AI outputs, document assumptions, and protect sensitive data.

Your expertise (must have)

• Fresh graduate or ‹ 1 year of relevant experience (internships, projects, or part-time roles count).

• Solid SQL fundamentals (joins, aggregations, basic window functions).

• One programming language for analysis (preferably Python ) with basic skills in:

• Data manipulation (tables/dataframes)

• Basic statistics (distributions, sampling intuition, confidence basics)

• Strong analytical thinking:

• Ability to define a problem, form hypotheses, validate data, and explain results.

• Strong attention to detail and commitment to accurate, reliable outputs.

• Ability to work effectively in a team-oriented environment.

Nice to have

• Exposure to data modeling concepts (star schema, slowly changing dimensions, metrics definition).

• Familiarity with modern analytics stacks (dbt, BigQuery, Snowflake, Looker, PowerBI, Tableau) through coursework or projects.

• Experience creating AI-ready data assets (clean semantic layers, metric definitions, data contracts, documentation, and evaluation or sanity-check checklists) is a plus.

• Experience using AI assistants responsibly to accelerate analysis or analytics engineering work (for example, SQL drafting, code scaffolding, documentation).

• Experience with version control (Git) or basic software engineering practices.

• Understanding of event tracking and product analytics (funnels, cohorts, retention).

• Knowledge of responsible data handling (PII basics, access controls, safe sharing).

What success looks like

• You can independently produce a well-structured analysis with clear assumptions and validation steps.

• You contribute at least one reliable dataset or transformation that becomes a shared building block for analytics.

• Stakeholders can answer more questions with self-serve and AI-assisted exploration, with less back-and-forth.

• A key dataset or metric you built becomes usable through AI tools with consistent answers (validated against a source-of-truth definition).

• You can spot when results look off, debug quickly, and explain the root cause.

• Global Platforms - Data

Source: Tamara careers page