Data Analyst

This is a remote position.

Company Mission:

Leegality is India’s first Document Infrastructure Platform - a radical new digital way for businesses to complete paperwork (agreements, forms and other legal documents). Over the last 7 years, Leegality has changed the way 2000+ Businesses do their paperwork from large enterprises like HDFC, SBI Cards, Federal Bank, ICICI Lombard, Axis Finance, Tata Capital etc. to high-growth companies like Razorpay, Rupeek, Cars24, Dunzo etc.

To see our impact on customers click here https://www.leegality.com/case-studies

Company Environment :

Leegality has an Employee Net Promoter Score of 97 - the highest on xto10x’s eNPS Survey for Q1 2022. The highest among 60+ notable startups.  This makes us, arguably, the most employee-loved startup in the country.

Creating a category-defining company - and changing the way businesses perform a critical function like paperwork - requires powerful marketing that resonates with people.

Responsibilities :

Core Analytics - 

• Respond promptly to data requests from diverse teams and stakeholders, using AI-assisted workflows to reduce turnaround time.
  

• Analyze and interpret complex datasets to extract meaningful, decision-ready insights.
  

• Develop and maintain interactive dashboards (Tableau / Metabase / Power BI) that clearly communicate KPIs and trends.
  

• Utilize SQL for efficient data extraction, transformation, and analysis—including AI-assisted query generation, optimization, and debugging.
  

• Employ advanced Excel / Google Sheets functionalities for data manipulation.
  

Data Infrastructure & Quality (Familiarity Level) - 

• Understand and monitor existing ETL pipelines to ensure data is syncing correctly from source databases (RDS/MySQL, Elasticsearch, etc.) into the data warehouse.
  

• Keep an eye on pipeline health, identify job failures, and work with the technical team to ensure data freshness for reporting.
  

• Write and run optimized queries on Amazon Redshift, with a basic understanding of how data warehouse tables are structured for performance.
  

• Maintain data quality through regular reconciliation checks between source systems and final reporting tables.
  

AI-Augmented Working -  

• Leverage AI assistants (Claude, Gemini, etc.) to accelerate SQL writing, data cleaning, exploratory analysis, and report drafting.
  

• Write effective prompts and build reusable AI workflows/templates for recurring analysis and reporting tasks.
  

• Automate repetitive reporting and data operations using scripts (Python / Apps Script) — with or without AI assistance.
  

• Critically validate AI-generated outputs: verify logic, check numbers against source data, and catch hallucinations before anything reaches stakeholders.
  

• Follow data privacy and security best practices when using AI tools — never expose sensitive or client data to unapproved platforms.
  

• Stay current with emerging AI/analytics tools and proactively suggest ways to improve team productivity.
  

Collaboration & Communication - 

• Collaborate closely with product, sales, tech, and customer success teams to understand their data needs.
  

• Provide analytical support that helps teams make data-driven decisions.
  

• Present findings to non-technical stakeholders in a clear and compelling manner.
  

• Communicate data-driven recommendations to support strategic initiatives.
  

• Engage in CEO-level interactions, offering data insights that contribute to high-level decision-making.
  

• Bring a dynamic and adaptable mindset, leveraging any previous startup experience.
  

Technical Skills :

Must Have - 

• SQL (strong proficiency — joins, CTEs, window functions).
  

• Experience extracting data from data warehouses (Amazon Redshift, Snowflake, or BigQuery).
  

• BI / Dashboarding tools (Tableau, Metabase, Power BI, or similar).
  

• Advanced Excel / Google Sheets.
  

• Hands-on experience using AI tools in an analytics workflow (prompt-writing ability for data tasks).
  

• Basic understanding of ETL concepts and how data pipelines work.
  

Good to Have - 

• Familiarity with AWS Glue, PySpark, or similar ETL tools (ability to read/understand basic scripts is a big plus).
  

• Python (pandas) for data analysis and automation.
  

• Broader AWS ecosystem exposure (S3, Secrets Manager, IAM, CloudWatch).
  

• Google Apps Script or similar automation experience.
  

• Experience with dual-source or streaming data pipelines (RDS + Elasticsearch, etc.).
  

• Familiarity with AI-powered BI features (natural-language querying, auto-insights).
  

• Basic understanding of APIs and connecting AI tools to data workflows.
  

Recruitment Process: 

• Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
  

• You will be contacted via email with the next steps upon being shortlisted.
  

• The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
  

• Final selection and CTC will be based on your overall performance and experience.
  

Requirements

Apply directly through our career page: https://careers.leegality.com/jobs/Careers

 For more information about us please visit our:

Website: https://www.leegality.com/

LinkedIn: https://www.linkedin.com/company/leegality/

Our Company and Culture: https://www.leegality.com/culture